Research Areas

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling

Jaideep Pathak, Yair Cohen, Piyush Garg, Peter Harrington, Noah Brenowitz, Dale Durran, Morteza Mardani, Arash Vahdat, Shaoming Xu, Karthik Kashinath, Mike Pritchard

GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators

Yuchen Hu, Chen Chen, Huck Yang, Ruizhe Li, Zhehuai Chen, Eng Siong Chng

ACL 2024

Align Your Steps: Optimizing Sampling Schedules in Diffusion Models

Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis

International Conference on Machine Learning (ICML) 2024

DoRA: Weight-Decomposed Low-Rank Adaptation

Shih-Yang Liu, Chien-Yi Wang, Hongxu Danny Yin, Pavlo Molchanov, Frank Wang, Kwang-Ting Cheng, Min-Hung Chen

International Conference on Machine Learning (ICML) 2024

Improving Hyperparameter Optimization with Checkpointed Model Weights

Nikhil Mehta, Jonathan Lorraine, Steve Masson, Ramanathan Arunachalam, Zaid Pervaiz Bhat, James Lucas, Arun George Zachariah

Large Language Model (LLM) for Standard Cell Layout Design Optimization

Chia-Tung (Mark) Ho, Haoxing (Mark) Ren

The First IEEE International Workshop on LLM-Aided Design (LAD'24)

Best Paper Award

Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models

Huan Ling, Seung Wook Kim, Antonio Torralba, Sanja Fidler, Karsten Kreis

CVPR 2024 (Highlight)

Nemotron-4 340B

An Empirical Study of Mamba-based Language Models

Roger Waleffe, Wonmin Byeon, Duncan Riach, Brandon Norick, Vijay Korthikanti, Tri Dao, Albert Gu, Ali Hatamizadeh, Sudhakar Singh, Deepak Narayanan, Garvit Kulshreshtha, Vartika Singh, Jared Casper, Jan Kautz, Mohammad Shoeybi, Bryan Catanzaro

https://arxiv.org/pdf/2406.07887

Full-colour 3D holographic augmented-reality displays with metasurface waveguides

Manu Gopakumar, Gun-Yeal Lee, Suyeon Choi, Brian Chao, Yifan Peng, Jonghyun Kim, Gordon Wetzstein

Nature

Large Language Models are Efficient Learners of Noise-Robust Speech Recognition

YuChen Hu, Chen Chen, Huck Yang, Ruizhe Li, Chao Zhang, Pin-Yu Chen, EnSiong Chng

ICLR 2024

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition

Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi, Pin-Yu Chen, Ensiong Chng, Huck Yang

ICLR 2024

WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space

Katja Schwarz, Seung Wook Kim, Jun Gao, Sanja Fidler, Andreas Geiger, Karsten Kreis

International Conference on Learning Representations (ICLR) 2024

FasterViT: Fast Vision Transformers with Hierarchical Attention

Ali Hatamizadeh, Greg Heinrich, Hongxu Danny Yin, Andrew Tao, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

International Conference on Learning Representations (ICLR) 2024

LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesis

Kevin Xie, Jonathan Lorraine, Tianshi Cao, Jun Gao, James Lucas, Antonio Torralba, Sanja Fidler, Xiaohui Zeng

ECCV

Novel Transformer Model Based Clustering Method for Standard Cell Design Automation

Chia-Tung (Mark) Ho, Ajay Chandna, David Guan, Alvin Ho, Minsoo Kim, Yaguang Li, Haoxing (Mark) Ren

International Symposium on Physical Design 2024

Best Paper Award

Generating images of rare concepts using pre-trained diffusion models

Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik

AAAI 2024

2023

Point-Cloud Completion with Pretrained Text-to-image Diffusion Models

Yoni Kasten, Ohad Rahamim, Gal Chechik

Convolutional State Space Models for Long-Range Spatiotemporal Modeling

Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon

Advances in Neural Information Processing Systems (NeurIPS) 2023

SceneScape: Text-Driven Consistent Scene Generation

Rafail Fridman, Amit Abecasis, Yoni Kasten, Tali Dekel

HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models

Chen Chen, YuChen Hu, Huck Yang, Sabato Marco Siniscalchi, Pin-Yu Chen, Ensiong Chng

Graph Metanetworks for Processing Diverse Neural Architectures

Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

ICLR

XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies

Xuanchi Ren, Jiahui Huang, Xiaohui Zeng, Ken Museth, Sanja Fidler, Francis Williams

Whispering LLaMA: A Cross-Modal Generative Error Correction Framework for Speech Recognition

Srijith Radhakrishnan, Huck Yang, Sumeer Khan, Rohit Kumar, Narsis Kiani, David Gomez-Cabrero, Jesper Tegnér

EMNLP

A Neural Receiver for 5G NR Multi-user MIMO

Sebastian Cammerer, Fayçal Aït Aoudia , Jakob Hoydis, Andreas Oeldemann, Andreas Roessler, Timo Mayer, Alex Keller

IEEE Globecom Workshops (GC Wkshps) 2023

Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling

Jakob Hoydis, Fayçal Aït Aoudia , Sebastian Cammerer, Merlin Nimier-David, Nikolaus Binder, Guillermo Marcus, Alex Keller

IEEE Globecom Workshops (GC Wkshps) 2023

CircuitOps: An ML Infrastructure Enabling Generative AI for VLSI Circuit Optimization

Rongjian Liang, Anthony Agnesina, Geraldo Pradipta, Vidya A. Chhabria, Haoxing (Mark) Ren

2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)

Imitating Task and Motion Planning with Visuomotor Transformers

Murtaza Dalal, Ajay Mandlekar, Caelan Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox

CoRL 2023

Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes

Anqi Gong, Sebastian Cammerer, Joseph M. Renes

International Conference on Quantum Information Processing (QIP) 2024

Human-In-The-Loop Task and Motion Planning for Imitation Learning

Ajay Mandlekar, Caelan Garrett, Danfei Xu, Dieter Fox

CoRL 2023

ChipNeMo: Domain-Adapted LLMs for Chip Design

Mingjie Liu, Teo Ene, Robert Kirby, Chris Cheng, Nathaniel Pinckney, Rongjian Liang, Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, Bonita Bhaskaran, Bryan Catanzaro, Arjun Chaudhuri, Sharon Clay, Bill Dally, Laura Dang, Parikshit Deshpande, Siddhanth Dhodhi, Sameer Halepete, Eric Hill, Jiashang Hu, Sumit Jain, Brucek Khailany, George Kokai, Kishor Kunal, Xiaowei Li, Charley Lind, Hao Liu, Stuart Oberman, Sujeet Omar, Sreedhar Pratty, Jonathan Raman, Ambar Sarkar, Zhengjiang Shao, Hanfei Sun, Pratik P Suthar, Varun Tej, Walker Turner, Kaizhe Xu, Haoxing (Mark) Ren

TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models

Tianshi Cao, Karsten Kreis, Sanja Fidler, Nicholas Sharp, Kangxue Yin

IEEE/CVF International Conference on Computer Vision (ICCV) 2023 (Oral)

ATT3D: Amortized Text-To-3D Object Synthesis

Jonathan Lorraine, Kevin Xie, Xiaohui Zeng, Chen-Hsuan Lin, Towaki Takikawa, Nicholas Sharp, Tsung-Yi Lin, Ming-Yu Liu, Sanja Fidler, James Lucas

DreamTeacher: Pretraining Image Backbones with Deep Generative Models

Daiqing Li, Huan Ling, Amlan Kar, David Acuna, Seung Wook Kim, Karsten Kreis, Antonio Torralba, Sanja Fidler

IEEE/CVF International Conference on Computer Vision (ICCV) 2023

Generative Novel View Synthesis with 3D-Aware Diffusion Models

Eric R. Chan, Koki Nagano, Matthew Chan, Alexander W. Bergman, Jeong Joon Park, Axel Levy, Miika Aittala, Shalini De Mello, Tero Karras, Gordon Wetzstein

International Conference on Computer Vision (ICCV) 2023

Oral

2D-3D Interlaced Transformer for Point Cloud Segmentation with Scene-Level Supervision

Cheng-Kun Yang, Min-Hung Chen, Yung-Yu Chaung, Yen-Yu Lin

IEEE/CVF International Conference on Computer Vision (ICCV) 2023

Interpretable Trajectory Prediction for Autonomous Vehicles via Counterfactual Responsibility

Kai-Chieh Hsu, Karen Leung, Yuxiao Chen, Jaime Fernandez Fisac, Marco Pavone

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Norm-guided latent space exploration for text-to-image generation

Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik

Syntactic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment

Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik

Online Overexposed Pixels Hallucination in Videos with Adaptive Reference Frame Selection

Oral presentation

Yazhou Xing, Amrita Mazumdar, Anjul Patney, Chao Liu, Hongxu Danny Yin, Qifeng Chen, Jan Kautz, Iuri Frosio

Differentially Private Diffusion Models

Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis

Transactions on Machine Learning Research (TMLR) 2023

Flexible Isosurface Extraction for Gradient-Based Mesh Optimization

Tianchang Shen, Jacob Munkberg, Jon Hasselgren, Kangxue Yin, Zian Wang, Wenzheng Chen, Zan Gojcic, Sanja Fidler, Nicholas Sharp, Jun Gao

ACM Transactions On Graphics (SIGGRAPH 2023)

Generalizing Shallow Water Simulations with Dispersive Surface Waves

Stefan Jeschke, Chris Wojtan

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models

Rinon Gal, Moab Arar, Yuval Atzmon, Amit Bermano, Gal Chechik, Daniel Cohen-Or

Walk on Stars: A Grid-Free Monte Carlo Method for PDEs with Neumann Boundary Conditions

Rohan Sawhney, Bailey Miller, Ioannis Gkioulekas, Keenan Crane

Data Free Learning of Reduced-Order Kinematics

Nicholas Sharp, Cristian Romero, David Levin, Alec Jacobson, Etienne Vouga, Paul Kry, Justin Solomon

IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu

KDD'23

Key-Locked Rank One Editing for Text-to-Image Personalization

Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon

Learning Physically Simulated Tennis Players from Broadcast Videos

Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, Sanja Fidler, Jason Peng, Kayvon Fatahalian

SIGGRAPH 2023 (Best Paper Honorable Mention)

Live 3D Portrait: Real-Time Radiance Fields for Single-Image Portrait View Synthesis

Alexander Trevithick, Matthew Chan, Michael Stengel, Eric R. Chan, Chao Liu, Zhiding Yu, Sameh Khamis, Manmohan Chandraker, Ravi Ramamoorthi, Koki Nagano

ACM Transactions On Graphics (SIGGRAPH 2023)

Micro-Mesh Construction

Andrea Maggiordomo, Henry Moreton, Marco Tarini

Interactive Hair Simulation on the GPU Using ADMM

Gilles Daviet

Guided Deep Kernel Learning

Idan Achituve, Gal Chechik, Ethan Fetaya

UAI 2023

Random-Access Neural Compression of Material Textures

Karthik Vaidyanathan, Marco Salvi, Bart Wronski, Tomas Akenine-Möller, Pontus Ebelin, Aaron Lefohn

A Hybrid Generator Architecture for Controllable Face Synthesis

SIGGRAPH 2023 Technical Papers Awards: Honorable Mention

Dann Mensah, Nam Hee Kim, Miika Aittala, Samuli Laine, Jaakko Lehtinen

SSIF: Single-shot Implicit Morphable Faces With Consistent Texture Parameterization

Connor Zhizhen Lin, Koki Nagano, Jan Kautz, Eric R. Chan, Umar Iqbal, Leonidas Guibas, Gordon Wetzstein, Sameh Khamis

Boundary Value Caching for Walk on Spheres

Bailey Miller, Rohan Sawhney, Keenan Crane, Ioannis Gkioulekas

Synthesizing Physical Character-Scene Interactions

Mohamed Hassan, Yunrong Guo, Tingwu Wang, Michael Black, Sanja Fidler, Xue Bin Peng

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models

Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or

AI-Mediated 3D Video Conferencing

Michael Stengel, Koki Nagano, Chao Liu, Matthew Chan, Alex Trevithick, Shalini De Mello, Jonghyun Kim, David Luebke, Amrita Mazumdar, Shengze Wang, Mayoore Jaiswal

ACM SIGGRAPH Emerging Technologies 2023

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models

Wenhao Ding, Gerry Che, Ding Zhao, Marco Pavone

International Conference on Machine Learning (ICML)

Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning

Zhutian Yang, Caelan Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Dieter Fox

Robotics: Science and Systems (RSS)

Meta-Policy Learning over Plan Ensembles for Robust Articulated Object Manipulation

Constantinos Chamzas, Caelan Garrett, Balakumar Sundaralingam, Lydia Kavraki, Dieter Fox

RSS 2023 Workshop on Learning for Task and Motion Planning

Late Breaking Results: Test Selection For RTL Coverage By Unsupervised Learning From Fast Functional Simulation

Rongjian Liang, Nathaniel Pinckney, Yuji Chai, Haoxing (Mark) Ren, Brucek Khailany

60th Design Automation Conference

Efficient Transformer Inference with Statically Structured Sparse Attention

Steve Dai, Hasan Genc, Rangharajan Venkatesan, Brucek Khailany

2023 60th ACM/IEEE Design Automation Conference (DAC)

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields

Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, Martin Wong

60th ACM/IEEE Design Automation Conference

Global Context Vision Transformers

Ali Hatamizadeh, Hongxu Danny Yin, Greg Heinrich, Jan Kautz, Pavlo Molchanov

International Conference on Machine Learning (ICML) 2023

Learning to Initiate and Reason in Event-Driven Cascading Processes

Yuval Atzmon, Eli Meirom, Shie Mannor, Gal Chechik

ICML 2023

Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles

Pasquale Antonante, Sushant Veer, Karen Leung, Xinshuo Weng, Luca Carlone, Marco Pavone

Robotics: Science and Systems (RSS) 2023

Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, Karsten Kreis

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularization

Jiawei Yang, Marco Pavone, Yue Wang

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models

Seung Wook Kim, Bradley Brown, Kangxue Yin, Karsten Kreis, Katja Schwarz, Daiqing Li, Robin Rombach, Antonio Torralba, Sanja Fidler

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Object Pose Estimation with Statistical Guarantees: Conformal Keypoint Detection and Geometric Uncertainty Propagation

Heng Yang, Marco Pavone

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Selected as a Highlight Paper

Learning Human-to-Robot Handovers from Point Clouds

Sammy Christen, Wei Yang, Claudia Pérez D’Arpino , Otmar Hilliges, Dieter Fox, Yu-Wei Chao

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Highlight

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris Kitani, Karsten Kreis, Sanja Fidler, Or Litany

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Hightlight top 10%

Zero-shot Pose Transfer for Unrigged Stylized 3D Characters

Jiashun Wang, Xueting Li, Sifei Liu, Shalini De Mello, Orazio Gallo, Xiaolong Wang, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Train Hard, Fight Easy: Robust Meta Reinforcement Learning

Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom

NeuroIPS 2023

Neuralangelo: High-Fidelity Neural Surface Reconstruction

Max Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H. Taylor, Mathias Unberath, Ming-Yu Liu, Chen-Hsuan Lin

CVPR 2023

The Best Inventions of 2023, TIME Magazine

Magic3D: High-Resolution Text-to-3D Content Creation

Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin

CVPR 2023 (Highlight)

Learning Autonomous Vehicle Safety Concepts from Demonstrations

Karen Leung, Sushant Veer, Edward Schmerling, Marco Pavone

American Control Conference (ACC) 2023

Tree-structured Policy Planning with Learned Behavior Models

Yuxiao Chen, Peter Karkus, Boris Ivanovic, Xinshuo Weng, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

BITS: Bi-level Imitation for Traffic Simulation

Danfei Xu, Yuxiao Chen, Boris Ivanovic, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

Guided Conditional Diffusion for Controllable Traffic Simulation

Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Gerry Che, Baishakhi Ray, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation

Yunzhi Lin, Thomas Müller, Jonathan Tremblay, Bowen Wen, Stephen Tyree, Alex Evans, Patricio A. Vela, Stan Birchfield

IEEE International Conference on Robotics and Automation (ICRA) 2023

Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning

Boris Ivanovic, James Harrison, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models

Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg

The International Conference on Robotics and Automation (ICRA)

Global and Reactive Motion Generation with Geometric Fabric Command Sequences

Weiming Zhi, Iretiayo Akinola, Karl Van Wyk, Nathan Ratliff, Fabio Ramos

IEEE International Conference on Robotics and Automation (ICRA) 2023

The Best Defense is a Good Offense: Adversarial Augmentation against Adversarial Attacks

Iuri Frosio, Jan Kautz

CVPR 2023

Subpixel Deblurring of Anti-Aliased Raster Clip Art

Jinfan Yang, Nicholas Vining, Shakiba Kheradmand, Nathan Carr, Leonid Sigal, Alla Sheffer

Computer Graphics Forum (Proc. Eurographics 2023)

CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation

Adithya Murali, Arsalan Mousavian, Clemens Eppner, Adam Fishman, Dieter Fox

International Conference on Robotics and Automation (ICRA)

CALM: Conditional Adversarial Latent Models for Directable Virtual Characters

Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng

Real-Time Neural Appearance Models

Tizian Zeltner, Fabrice Rousselle, Andrea Weidlich, Petrik Clarberg, Jan Novák, Benedikt Bitterli, Alex Evans, Tomáš Davidovič, Simon Kallweit, Aaron Lefohn

TOG (Presented at SIGGRAPH 2024)

Recursive Control Variates for Inverse Rendering

Baptiste Nicolet, Fabrice Rousselle, Jan Novák, Alexander Keller, Wenzel Jakob, Thomas Müller

GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation

Chenhongyi Yang, Jiarui Xu, Shalini De Mello, Elliot J. Crowley, Xiaolong Wang

International Conference on Learning Representations (ICLR) 2023

Notable top 25%, Oral

Robust and Controllable Object-Centric Learning through Energy-based Models

Ruixiang Zhang, Gerry Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull

International Conference on Learning Representations (ICLR) 2023

DREAM-GAN: Advancing DREAMPlace towards Commercial-Quality using Generative Adversarial Learning

Yi-Chen Lu, Haoxing (Mark) Ren, Hao-Hsiang Hsiao, Sung Kyu Lim

NVCell 2: Routability-Driven Standard Cell Layout in Advanced Nodes with Lattice Graph Routability Model

Chia-Tung (Mark) Ho, Alvin Ho, Matt Fojtik, Minsoo Kim, Shang Wei, Yaguang LI, Brucek Khailany, Haoxing (Mark) Ren

Reinforcement Learning Guided Detailed Routing for Custom Circuits

Hao Chen, Kai-Chieh Hsu, Walker Turner, Po-Hsuan Wei, Keren Zhu, David Z. Pan, Haoxing (Mark) Ren

AutoDMP: Automated DREAMPlace-based Macro Placement

Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Haoxing (Mark) Ren

Joint Neural Denoising of Surfaces and Volumes

Nikolai Hofmann, Jon Hasselgren, Jacob Munkberg

I3D 2023

Equivariant Architectures for Learning in Deep Weight Spaces

Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML 2023

Enabling Scalable AI Computational Lithography with Physics-Inspired Models

Haoyu Yang, Haoxing (Mark) Ren

2023 28th Asia and South Pacific Design Automation Conference (ASP-DAC)

Target-free Text-guided Image Manipulation

Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang

AAAI 2023

Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis

Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang

AAAI 2023

A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm

Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany

Journal of Solid-State Circuits

Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning

Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler

AAMAS 2023

Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond

Cheng-Yen Hsieh, Chih-Jung Chang, Fu-En Yang, Frank Wang

WACV 2023

2022

Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles

Alec Farid, Sushant Veer, Boris Ivanovic, Karen Leung, Marco Pavone

Conference on Robot Learning (CoRL) 2022

DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone

Conference on Robot Learning (CoRL) 2022

Robust Trajectory Prediction against Adversarial Attacks

Yulong Cao, Danfei Xu, Xinshuo Weng, Z. Morely Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone

Conference on Robot Learning (CoRL) 2022

Selected for Oral Presentation

Efficient Arithmetic Block Identification with Graph Learning and Network-flow

Ziyi Wang, Zhuolun He, Chen Bai, Haoyu Yang, Bei Yu

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Deep Learning-Based Synchronization for Uplink NB-IoT

Fayçal Aït Aoudia , Jakob Hoydis, Sebastian Cammerer, Matthijs Van keirsbilck, Alex Keller

IEEE Global Communications Conference 2022

Graph Neural Networks for Channel Decoding

Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia , Alex Keller

IEEE Globecom Workshops (GC Wkshps) 2022

An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design

Mingjie Liu, Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Selim Dogru, Anima Anandkumar, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren

Workshop on ML for Systems at NeurIPS

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression

Jiaqi Gu, Ben Keller, Jean Kossaifi, Anima Anandkumar, Brucek Khailany, David Z. Pan

Workshop on ML for Systems at NeurIPS

Spotlight Paper

LNS-Madam: Low-Precision Training in Logarithmic Number System Using Multiplicative Weight Update

Jiawei Zhao, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Mustafa Ali, Ming-Yu Liu, Brucek Khailany, William Dally, Anima Anandkumar

IEEE Transactions on Computers (Volume: 71, Issue: 12, 01 December 2022)

Motion Policy Networks

Adam Fishman, Adithya Murali, Clemens Eppner, Bryan Peele, Byron Boots, Dieter Fox

Conference on Robot Learning (CoRL), 2022

"This is my unicorn, Fluffy": Personalizing frozen vision-language representations

Niv Cohen, Rinon Gal, Eli Meirom, Gal Chechik, Yuval Atzmon

ECCV 2022

Elucidating the Design Space of Diffusion-Based Generative Models

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine

NeurIPS 2022 (oral)

NeurIPS Outstanding Paper

LION: Latent Point Diffusion Models for 3D Shape Generation

Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis

Neural Information Processing Systems (NeurIPS) 2022

GENIE: Higher-Order Denoising Diffusion Solvers

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Neural Information Processing Systems (NeurIPS) 2022

Paraphrasing Is All You Need for Novel Object Captioning

Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Frank Wang

NeurIPS 2022

SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion

Sheng-Yu Huang, Hao-Yu Hsu, Yu-Chiang Frank Wang

NeurIPS 2022

Demystifying Map Space Exploration for NPUs

Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna

International Symposium on Workload Characterization (IISWC)

Towards Adaptive Digital Self-Interference Cancellation in Full-Duplex Wireless Transceivers: APSM vs. Neural Networks

M. Hossein Attar, Kaixin Chang, Ramez Askar, Slawomir Stanczak, Sebastian Cammerer, Guillermo Marcus, Alex Keller

Asilomar Conference on Signals, Systems, and Computers 2022

TransSizer: A Novel Transformer-Based Fast Gate Sizer

Siddhartha Nath, Geraldo Pradipta, Corey Hu, Tian Yang, Brucek Khailany, Haoxing (Mark) Ren

2022 International Conference on Computer-Aided Design

TAG: Learning Circuit Spatial Embedding from Layouts

Keren Zhu, Hao Chen, Walker Turner, George F. Kokai, Po-Hsuan Wei, David Z. Pan, Haoxing (Mark) Ren

2022 International Conference on Computer-Aided Design

Why are Graph Neural Networks Effective for EDA Problems?

Haoxing (Mark) Ren, Siddhartha Nath, Yanqing Zhang, Hao Chen, Mingjie Liu

2022 International Conference on Computer-Aided Design

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Adrien Gaidon, Marco Pavone

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022

Augmenting Legacy Networks for Flexible Inference.

Jason Clemons, Iuri Frosio, Maying Shen, Jose M. Alvarez, Steve Keckler

Workshop on Computational Aspects of Deep Learning (CADL)

AdvDO: Realistic Adversarial Attacks for Trajectory Prediction

Yulong Cao, Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone

European Conference on Computer Vision (ECCV) 2022

LANA: Latency Aware Network Acceleration

Pavlo Molchanov, Jimmy Hall, Hongxu Danny Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat

European Conference on Computer Vision (ECCV), 2022

Generative Adversarial Neural Operators

Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar, Zachary E. Ross, Kamyar Azizzadenesheli

Transactions on Machine Learning Research

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning

Guy Tenneholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik

ICLR

Placement Optimization via PPA-Directed Graph Clustering

Yi-Chen Lu, Tian Yang, Sung Kyu Lim, Haoxing (Mark) Ren

MLCAD '22: Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD

XT-PRAGGMA: Crosstalk Pessimism Reduction Accessible by GPU Gate-level Simulations and Machine Learning

Vidya Chhabria, Ben Keller, Yanqing Zhang, Sandeep Vollala, Sreedhar Patty, Haoxing (Mark) Ren, Brucek Khailany

MLCAD '22: Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD

GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access

Daniel Schäufele, Guillermo Marcus, Nikolaus Binder, Matthias Mehlhose, Alex Keller, Slawomir Stańczak

2022 30th European Signal Processing Conference (EUSIPCO)

Self Adaptive Reconfigurable Arrays (SARA): Learning Flexible GEMM Accelerator Configuration and Mapping-space using ML

Ananda Samajdar, Eric Qin, Michael Pellauer, Tushar Krishna

Detecting Viewer-Perceived Intended Vector Sketch Connectivity

Jerry Yin, Chenxi Liu, Rebecca Liu, Nicholas Vining, Helge Rhodin, Alla Sheffer

Time-multiplexed Neural Holography: A Flexible Framework for Holographic Near-eye Displays with Fast Heavily-quantized Spatial Light Modulators

Suyeon Choi, Manu Gopakumar, Yifan Peng, Jonghyun Kim, Matthew O'Toole, Gordon Wetzstein

Holographic Glasses for Virtual Reality

Jonghyun Kim, Manu Gopakumar, Suyeon Choi, Yifan Peng, Ward Lopes, Gordon Wetzstein

SIGGRAPH 2022

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or

ICLR 2023

Top 25%

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

Thomas Müller, Alex Evans, Christoph Schied, Alex Keller

Unbiased Inverse Volume Rendering With Differential Trackers

Best Technical Paper, SIGGRAPH 2022, THE BEST INVENTIONS OF 2022, TIME

Merlin Nimier-David, Thomas Müller, Alex Keller, Wenzel Jakob

Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training

Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Brucek Khailany, William Dally

2022 International Conference on Machine Learning (ICML)

Adaptive Neural Network-based OFDM Receivers

Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer, Takayuki Shimizu, Hongsheng Lu, Stephan ten Brink

IEEE International Workshop on Signal Processing Advances in Wireless Communic…

Diffusion Models for Adversarial Purification

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar

International Conference on Machine Learning (ICML), 2022

GPU-Accelerated Partially Linear Multiuser Detection for 5G and Beyond URLLC Systems

Matthias Mehlhose, Guillermo Marcus, Daniel Schäufele, Daniyal Amir Awan, Nikolaus Binder, Martin Kasparick, Renato L. G. Cavalcante, Sławomir Stanćzak , Alex Keller

IEEE Access

Correcting Robot Plans with Natural Language Feedback

Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis, Chris Paxton, Tucker Hermans, Antonio Torralba, Jacob Andreas, Dieter Fox

Robotics Science and Systems (RSS) 2022

ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning

Yuxiao Chen, Boris Ivanovic, Marco Pavone

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Whose Track Is It Anyway? Improving Robustness to Tracking Errors with Affinity-Based Prediction

Xinshuo Weng, Boris Ivanovic, Kris Kitani, Marco Pavone

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Polymorphic-GAN: Generating Aligned Samples across Multiple Domains with Learned Morph Maps

Seung Wook Kim, Karsten Kreis, Daiqing Li, Antonio Torralba, Sanja Fidler

Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral)

BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations

Daiqing Li, Huan Ling, Seung Wook Kim, Karsten Kreis, Adela Barriuso, Sanja Fidler, Antonio Torralba

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022

GroupViT: Semantic Segmentation Emerges from Text Supervision

Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, Xiaolong Wang

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Efficient Geometry-aware 3D Generative Adversarial Networks

Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, Gordon Wetzstein

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Oral

FreeSOLO: Learning to Segment Objects without Annotations

Xinlong Wang, Zhiding Yu, Shalini De Mello, Jan Kautz, Anima Anandkumar, Chunhua Shen, Jose M. Alvarez

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

A 17–95.6 TOPS/W Deep Learning Inference Accelerator with Per-Vector Scaled 4-bit Quantization for Transformers in 5nm

Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, William Dally, Tom Gray, Brucek Khailany

2022 Symposium on VLSI Technology & Circuits Digest of Technical Papers

Optimizing tensor network contraction using reinforcement learning

Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

International Conference on Machine Learning, PMLR 162:15278-15292, 2022

Injecting Planning-Awareness into Prediction and Detection Evaluation

Boris Ivanovic, Marco Pavone

IEEE Intelligent Vehicles Symposium (IV) 2022

MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation

Xinshuo Weng, Boris Ivanovic, Marco Pavone

IEEE Intelligent Vehicles Symposium (IV) 2022

Propagating State Uncertainty Through Trajectory Forecasting

Boris Ivanovic, Yifeng Lin, Shubham Shrivastava, Punarjay Chakravarty, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2022

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

Rinon Gal, Or Patashnik, Haggai Maron, Amir Bermano, Gal Chechik, Daniel Cohen-Or

SIGGRAPH 2022

MatBuilder: Mastering Sampling Uniformity Over Projections

Loïs Paulin, Nicolas Bonneel, David Coeurjolly, Jean-Claude Iehl, Alex Keller, Victor Ostromoukhov

Accelerated Policy Learning with Parallel Differentiable Simulation

Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin

International Conference on Learning Representations (ICLR) 2022

Artificial Neural Networks generated by Low Discrepancy Sequences

Matthijs Van keirsbilck, Alex Keller

arxiv link

A Dataset and Explorer for 3D Signed Distance Functions

Towaki Takikawa, Andrew Glassner, Morgan McGuire

Journal of Computer Graphics Techniques

Neural Fields in Visual Computing and Beyond

Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar

Computer Graphics Forum (Eurographics 2022)

Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design

Ye Yuan, Yuda Song, Zhengyi Luo, Wen Sun, Kris Kitani

International Conference on Learning Representations (ICLR) 2022 (Oral)

Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators

"This is my unicorn, Fluffy": Personalizing frozen vision-language representations

Niv Cohen, Rinon Gal, Gal Chechik, Yuval Atzmon

ECCV 2022

Oral

Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Jakob Hoydis, Sebastian Cammerer, Fayçal Aït Aoudia , Avinash Vem, Nikolaus Binder, Guillermo Marcus, Alex Keller

DefGraspSim: Physics-Based Simulation of Grasp Outcomes on 3D Deformable Objects

Isabella Huang, Yashraj Narang, Clemens Eppner, Balakumar Sundaralingam, Miles Macklin, Ruzena Bajcsy, Tucker Hermans, Dieter Fox

IEEE Robotics and Automation Letters

DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators

Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna

Design, Automation & Test in Europe (DATE)

Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks

Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Mark Kilgard, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing (Mark) Ren

2022 Design Automation Conference

Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

Jingkai Chen, Jiaoyang Li, Yijiang Huang, Caelan Garrett, Dawei Sun, Chuchu Fan, Andreas Hofmann, Caitlin Mueller, Sven Koenig, Brian Williams

https://arxiv.org/abs/2203.02475

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Tim Dockhorn, Arash Vahdat, Karsten Kreis

International Conference on Learning Representations (ICLR) 2022 (Spotlight)

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Zhisheng Xiao, Karsten Kreis, Arash Vahdat

International Conference on Learning Representations (ICLR) 2022 (Spotlight)

Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators

Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar

Transactions on Architecture and Code Optimization (TACO)

Reinforcement Learning for Datacenter Congestion Control

Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mendelbaum, Doron Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor

IAAI 2022

Machine Learning and Algorithms: Let Us Team Up for EDA

Haoxing (Mark) Ren, Brucek Khailany, Matt Fojtik, Yanqing Zhang

IEEE Design & Test

2021

ATISS: Autoregressive Transformers for Indoor Scene Synthesis

Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler

Neural Information Processing Systems (NeurIPS) 2021

EditGAN: High-Precision Semantic Image Editing

Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler

Neural Information Processing Systems (NeurIPS) 2021

Alias-Free Generative Adversarial Networks

Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila

NeurIPS 2021

Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers

Jacob R. Stevens, Rangharajan Venkatesan, Steve Dai, Brucek Khailany, Anand Raghunathan

Design Automation Conference (DAC) 2021

NVCell: Standard Cell Layout in Advanced Technology Nodes with Reinforcement Learning

Haoxing (Mark) Ren, Matt Fojtik, Brucek Khailany

Design Automation Conference (DAC) 2021 (Invited special session paper)

KAMA: 3D Keypoint Aware Body Mesh Articulation

Umar Iqbal, Kevin Xie, Kelly Guo, Jan Kautz, Pavlo Molchanov

International Conference on 3D Vision

Standard vs. Learning-based Codecs for Real Time Endoscopic Video Transmission

Iuri Frosio, Aldo Marzullo, Martina Golini, Elena De Momi, Michele Catellani, Francesco Calimeri, Giuseppe Fiameni

AIABI-2021 Italian Workshop on Artificial Intelligence and Applications for Bus…

Extracting Triangular 3D Models, Materials, and Lighting From Images

Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, Sanja Fidler

CVPR 2022 (Oral)

Noise-Aware Video Saliency Prediction

Ekta Prashnani, Orazio Gallo, Joohwan Kim, Josef Spjut, Pradeep Sen, Iuri Frosio

The British Machine Vision Conference (BMVC) - 2021

Score-based Generative Modeling in Latent Space

Arash Vahdat, Karsten Kreis, Jan Kautz

Neural Information Processing Systems (NeurIPS) 2021

A Contrastive Learning Approach for Training Variational Autoencoder Priors

Jyoti Aneja, Alexander Schwing, Jan Kautz, Arash Vahdat

Neural Information Processing Systems (NeurIPS) 2021

Controllable and Compositional Generation with Latent-Space Energy-Based Models

Weili Nie, Arash Vahdat, Anima Anandkumar

Neural Information Processing Systems (NeurIPS) 2021

Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence

Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis

Neural Information Processing Systems (NeurIPS) 2021

Speckle-free holography with partially coherent light sources and camera-in-the-loop calibration

Yifan Peng, Suyeon Choi, Jonghyun Kim, Gordon Wetzstein

Science Advances

Graph Learning-Based Arithmetic Block Identification

Zhuolun He, Ziyi Wang, Chen Bai, Haoyu Yang, Bei Yu

IEEE/ACM International Conference on Computer-Aided Design

Optimizing Selective Protection for CNN Resilience

Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler

International Symposium on Software Reliability Engineering (ISSRE)

Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction

Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik

Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators

Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna

Parallel Architectures and Compilation Techniques (PACT)

Compressing 1D Time-Channel Separable Convolutions using Sparse Random Ternary Matrices

Goncalo Mordido, Matthijs Van keirsbilck, Alex Keller

Interspeech 2021

SiP-ML: high-bandwidth optical network interconnects for machine learning training

Mehrdad Khani, Manya Ghobadi, Mohammad Alizadeh, Ziyi Zhu, Madeleine Glick, Keren Bergman, Amin Vahdat, Benjamin Klenk, Eiman Ebrahimi

SIGCOMM '21: Proceedings of the 2021 ACM SIGCOMM 2021 Conference

Known unknowns: Learning novel concepts using exploratory reasoning-by-elimination

Harsh Agrawal, Eli Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Inte…

Oral

Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles

Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar

IEEE Intelligent Vehicles Symposium (IV)

Improving Long-read Consensus Sequencing Accuracy with Deep Learning

Avantika Lal, Michael Brown, Rahul Mohan, Joyjit Daw, James Drake, Johnny Israeli

Biorxiv

NeRF-Tex: Neural Reflectance Field Textures

Hendrik Baatz, Jonathan Granskog, Marios Papas, Fabrice Rousselle, Jan Novák

Eurographics Symposium on Rendering (EGSR)

Neural Scene Graph Rendering

Jonathan Granskog, Till Schnabel, Fabrice Rousselle, Jan Novák

ACM Transactions on Graphics

Real-time Neural Radiance Caching for Path Tracing

Thomas Müller, Fabrice Rousselle, Jan Novák, Alex Keller

ACM Transactions on Graphics

Learning to Track Instances without Video Annotations

Yang Fu, Sifei Liu, Umar Iqbal, Shalini De Mello, Humphrey Shi, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021

Oral

Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization

Daiqing Li, Junlin Yang, Karsten Kreis, Antonio Torralba, Sanja Fidler

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021

One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing

Ting-Chun Wang, Arun Mallya, Ming-Yu Liu

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes

Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, Sanja Fidler

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021

Weakly-Supervised Physically Unconstrained Gaze Estimation

Rakshit Kothari, Shalini De Mello, Umar Iqbal, Wonmin Byeon, Seonwook Park, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021

Oral

Controlling graph dynamics with reinforcement learning and graph neural networks

Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

ICML 2021

From local structures to size generalization in graph neural networks

Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron

ICML 2021

VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models

Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat

International Conference on Learning Representations (ICLR) 2021 (Spotlight)

ACRONYM: A Large-Scale Grasp Dataset Based on Simulation

Clemens Eppner, Arsalan Mousavian, Dieter Fox

2021 IEEE International Conference on Robotics and Automation (ICRA)

Simba: scaling deep-learning inference with chiplet-based architecture

Yakun Sophia Shao, Jason Clemons, Rangharajan Venkatesan, Brian Zimmer, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Brucek Khailany, Steve Keckler

Communications of the ACM

ACM Research Highlight

Contrastive Syn-to-Real Generalization

Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez, Zhangyang Wang, Anima Anandkumar

International Conference on Learning Representations (ICLR) 2021

GAMMA: Exploiting Gustavson’s Algorithm to Accelerate Sparse Matrix Multiplication

Guowei Zhang, Nithya Attaluri, Joel Emer, Daniel Sanchez

International Conference on Architectural Support for Programming Languages and…

Appearance-Driven Automatic 3D Model Simplification

Jon Hasselgren, Jacob Munkberg, Jaakko Lehtinen, Miika Aittala, Samuli Laine

EGSR 2021

VS-QUANT: Per-Vector Scaled Quantization for Accurate Low-Precision Neural Network Inference

Steve Dai, Rangharajan Venkatesan, Haoxing (Mark) Ren, Brian Zimmer, William Dally, Brucek Khailany

MLSys 2021

Auxiliary Learning by Implicit Differentiation

Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

ICLR 2021

On the Universality of Rotation Equivariant Point Cloud Networks

Nadav Dym, Haggai Maron

ICLR 2021

Learning the Pareto Front with Hypernetworks

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik

ICLR | 2021

Learning Sparse Matrix Row Permutations for Efficient SpMM on GPU Architectures

Atefeh Mehrabi, Donghyuk Lee, Niladrish Chatterjee, Danial J. Sorin, Benjamin C. Lee, Mike O'Connor

International Symposium on Performance Analysis of Systems and Software (ISPASS)

Robust Vision-Based Cheat Detection in Competitive Gaming

Aditya Jonnalagadda, Iuri Frosio, Seth Schenider, Morgan McGuire, Joohwan Kim

I3D ’21

Interactive Path Tracing and Reconstruction of Sparse Volumes

Nikolai Hofmann, Jon Hasselgren, Petrik Clarberg, Jacob Munkberg

Proceedings of the ACM on Computer Graphics and Interactive Techniques

Best Paper Presentation, i3D 2021

Deep Learning-based Enhancement of Epigenomics Data with AtacWorks

Avantika Lal, Zachary D Chiang, Nikolai Yakovenko, Fabiana M Duarte, Johnny Israeli, Jason D Buenrostro

Nature Communications

Making Convolutions Resilient via Algorithm-Based Error Detection Techniques

Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler

IEEE Transactions on Dependable and Secure Computing (TDSC)

Heterogeneous Dataflow Accelerators for Multi-DNN Workloads

Hyoukjun Kwon, Liangzhen Lai, Michael Pellauer, Tushar Krishna, Yu-Hsin Chen, Vikas Chandra

International Symposium on High-Performance Computer Architecture (HPCA)

MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification

Vidya A. Chhabria, Yanqing Zhang, Haoxing (Mark) Ren, Ben Keller, Brucek Khailany, Sachin S. Sapatnekar

2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)

Parasitic-Aware Analog Circuit Sizing with Graph Neural Networks and Bayesian Optimization

Mingjie Liu, Walker Turner, George Kokai, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren

2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)

Planning and Learning with Adaptive Lookahead

Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal

Federated Learning with Heterogeneous Architectures using Graph HyperNetworks

Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler

Standard Cell Routing with Reinforcement Learning and Genetic Algorithm in Advanced Technology Nodes

Haoxing (Mark) Ren, Matt Fojtik

26th Asia and South Pacific Design Automation Conference (ASP-DAC) 2021

Self-Supervised Learning for Domain Adaptation on Point-Clouds

Idan Achituve, Haggai Maron, Gal Chechik

Winter Conference on Applications of Computer Vision (WACV), 2021

From Generalized Zero-Shot Learning to Long-Tail with Class Descriptors

Dvir Samuel, Yuval Atzmon, Gal Chechik

Winter Conference on Applications of Computer Vision (WACV) 2021

Acting in Delayed Environments with Non-Stationary Markov Policies

Esther Derman, Gal Dalal, Shie Mannor

ICLR 2021

Flexion: A Quantitative Metric for Flexibility in DNN Accelerators

Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna

IEEE Computer Architecture Letters (CAL)

2020

NVCell: Generate Standard Cell Layout in Advanced Technology Nodes with Reinforcement Learning

Haoxing (Mark) Ren, Matt Fojtik, Brucek Khailany

Workshop on ML for Systems at NeurIPS

Online Adaptation for Consistent Mesh Reconstruction in the Wild

Xueting Li, Sifei Liu, Shalini De Mello, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz

Neural Information Processing Systems (NeurIPS) 2020

Set2Graph: Learning Graphs From Sets

Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman

Conference on Neural Information Processing Systems (NeurIPS 2020)

Self-Learning Transformations for Improving Gaze and Head Redirection

Yufeng Zheng, Seonwook Park, Xucong Zhang, Shalini De Mello, Otmar Hilliges

Neural Information Processing Systems (NeurIPS) 2020

A Causal View of Compositional Zero-Shot Recognition

Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik

Neural Information Processing Systems (NeurIPS) 2020 (Spotlight)

Convolutional Tensor-Train LSTM for Spatio-Temporal Learning

Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar

Advances in Neural Information Processing Systems (NeurIPS)

Training Generative Adversarial Networks with Limited Data

Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila

NeurIPS 2020

Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning

Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar

Conference on Neural Information Processing Systems (NeurIPS) 2020 (Spotlight)

Neural Networks with Recurrent Generative Feedback

Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar

Conference on Neural Information Processing Systems (NeurIPS) 2020

Learning Deformable Tetrahedral Meshes for 3D Reconstruction

Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire

NeurIPS

Variational Amodal Object Completion

Huan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler

Neural Information Processing Systems (NeurIPS) 2020

Accelerating Reinforcement Learning through GPU Atari Emulation

Iuri Frosio, Steven Dalton

Advances in Neural Information Processing Systems 33 (NeurIPS 2020)

Neural FFTs for Universal Texture Image Synthesis

Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro

NeurIPS 2020

Neural Control Variates

Thomas Müller, Fabrice Rousselle, Alex Keller, Jan Novák

ACM Transactions on Graphics (SIGGRAPH Asia)

ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization

Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik, Reut Tsarfaty

Findings of EMNLP

Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles

Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar

IEEE International Workshop on Automotive Reliability & Test (ART)

Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles

Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar

IEEE Automotive Reliability and Test Workshop

Modular Primitives for High-Performance Differentiable Rendering

Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila

ACM Transactions on Graphics 39(6) (Proc. SIGGRAPH Asia 2020)

Learning Object Permanence from Video

Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik

ECCV 2020

A Programmable Approach to Neural Network Compression

Vinu Joseph, Ganesh L. Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg

IEEE Micro: Special Issue on Machine Learning for Systems

Accelerating Chip Design with Machine Learning

Brucek Khailany, Haoxing (Mark) Ren, Steve Dai, Saad Godil, Ben Keller, Robert Kirby, Alicia Klinefelter, Rangharajan Venkatesan, Yanqing Zhang, Bryan Catanzaro, William Dally

IEEE Micro

HarDNN: Fine-Grained Vulnerability Evaluation and Protection for Convolutional Neural Networks

Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler

SRC TECHCON

UNAS: Differentiable Architecture Search Meets Reinforcement Learning

Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021

UFO2: A Unified Framework towards Omni-supervised Object Detection

Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Alexander G. Schwing, Jan Kautz

European Conference on Computer Vision (ECCV) 2020

Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification

Yang Zou, Xiaodong Yang, Zhiding Yu, B. V. K. Vijaya Kumar, Jan Kautz

European Conference on Computer Vision (ECCV) 2020 (Oral)

World-Consistent Video-to-Video Synthesis

Arun Mallya, Ting-Chun Wang, Karan Sapra, Ming-Yu Liu

ECCV

Self-supervised Single-view 3D Reconstruction via Semantic Consistency

Xueting Li, Sifei Liu, Kihwan Kim, Shalini De Mello, Varun Jampani, Ming-Hsuan Yang, Jan Kautz

European Conference on Computer Vision (ECCV) 2020

Weakly-Supervised 3D Hand Pose Estimation via Biomechanical Constraints

Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Otmar Hilliges, Jan Kautz

European Conference on Computer Vision, 2020

ParaGraph: Layout Parasitics and Device Parameter Prediction using Graph Neural Networks

Haoxing (Mark) Ren, George Kokai, Walker Turner, Ting-Sheng Ku

Design Automation Conference (DAC) 2020

Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks

Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Reddy Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh

International Symposium on Microarchitecture (MICRO)

GRANNITE: Graph Neural Network Inference for Transferable Power Estimation

Yanqing Zhang, Haoxing (Mark) Ren, Brucek Khailany

Design Automation Conference (DAC) 2020

Semi-Supervised StyleGAN for Disentanglement Learning

Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar

International Conference on Machine Learning (ICML) 2020

Angular Visual Hardness

Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Anima Anandkumar

International Conference on Machine Learning (ICML) 2020

On Learning Sets of Symmetric Elements

Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

International Conference on Machine Learning (ICML) 2020

Outstanding Paper, ICML 2020

Learning Algebraic Multigrid Using Graph Neural Networks

Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh

International Conference on Machine Learning (ICML) 2020

NVAE: A Deep Hierarchical Variational Autoencoder

Arash Vahdat, Jan Kautz

Neural Information Processing Systems (NeurIPS) 2020 (Spotlight)

Compositional Neural Scene Representations for Shading Inference

Jonathan Granskog, Fabrice Rousselle, Marios Papas, Jan Novák

ACM Transaction on Graphics (SIGGRAPH)

ML-driven Malware that Targets AV Safety

Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer

International Conference on Dependable Systems and Networks (DSN)

PyTorchFI: A Runtime Perturbation Tool for DNNs

Abdulrahman Mahmoud, Neeraj Aggarwal, Alex Nobbe, Jose Rodrigo Sanchez Vicarte, Sarita V. Adve, Christopher W. Fletcher, Iuri Frosio, Siva Hari

Workshop on Dependable and Secure Machine Learning

DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement

Yibo Lin, Zixuan Jiang, Jiaqi Gu, Wuxi Li, Shounak Dhar, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (…

2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award

Contrastive Learning for Weakly Supervised Phrase Grounding

Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem

European Conference on Computer Vision (ECCV) 2020 (Spotlight)

Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Yong Jae Lee, Alexander G. Schwing, Jan Kautz

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Regularizing Neural Networks via Minimizing Hyperspherical Energy

Weiyang Liu, Rongmei Lin, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Bi3D: Stereo Depth Estimation via Binary Classifications

Abhishek Badki, Alejandro Troccoli, Kihwan Kim, Jan Kautz, Pradeep Sen, Orazio Gallo

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Meshlet Priors for 3D Mesh Reconstruction

Abhishek Badki, Orazio Gallo, Jan Kautz, Pradeep Sen

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Analyzing and Improving the Image Quality of StyleGAN

Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila

CVPR 2020

Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths

Jae shin Yoon, Kihwan Kim, Orazio Gallo, Hyunsoo Park, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Self-Supervised Viewpoint Learning From Image Collections

Siva Karthik Mustikovela, Varun Jampani, Shalini De Mello, Sifei Liu, Umar Iqbal, Carsten Rother, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Two-shot Spatially-varying BRDF and Shape Estimation

Mark Boss, Varun Jampani, Kihwan Kim, Hendrik P.A. Lensch, Jan Kautz

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Monte Carlo Gradient Quantization

Goncalo Mordido, Matthijs Van keirsbilck, Alex Keller

CVPR2020 Workshop

Making Convolutions Resilient via Algorithm-Based Error Detection Techniques

Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler

Learning Canonical Representations for Scene Graph to Image Generation

Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson

ECCV 2020

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

Esha Chouske, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Steve Keckler

International Symposium on Computer Architecture (ISCA)

Self-supervised 6D Object Pose Estimation for Robot Manipulation

Xinke Deng, Yu Xiang, Arsalan Mousavian, Clemens Eppner, Timothy Bretl, Dieter Fox

2020 IEEE International Conference on Robotics and Automation (ICRA)

An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives

Benjamin Klenk, Ted Jiang, Greg Thorson, Larry Dennison

International Symposium on Computer Architecture (ISCA)

How to close sim-real gap? transfer with segmentation!

Mengyuan Yan, Qingyun Sun, Iuri Frosio, Stephen Tyree, Jan Kautz

arxiv

ML-driven Malware that Targets AV Safety

Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer

MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings

Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar

IEEE Micro (Issue: Top Picks of the 2019 Computer Architecture Conferences)

Genome Variant Calling with a Deep Averaging Network

Nikolai Yakovenko, Avantika Lal, Johnny Israeli, Bryan Catanzaro

SymGAN: Orientation Estimation without Annotation for Symmetric Objects

Phil Ammirato, Jonathan Tremblay, Ming-Yu Liu, Alexander Berg, Dieter Fox

WACV

Neurreg: Neural registration and its application to image segmentation

Wentao Zhu, Andriy Myronenko, Ziyue Xu, Wenqi Li, Holger Roth, Yufang Huang, Fausto Milletari, Daguang Xu

WACV

HarDNN: Feature Map Vulnerability Evaluation in CNNs

Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler

On the Distance between Two Neural Networks and the Stability of Learning

Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu

Neural Information Processing Systems (NeurIPS) 2020

Domain Stylization: A Fast Covariance Matching Framework towards Domain Adaptation

Aysegul Dundar, Ming-Yu Liu, Zhiding Yu, Ting-Chun Wang, John Zedlewski, Jan Kautz

IEEE Transactions on Pattern Analysis and Machine Intelligence

A 0.32–128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm

Brian Zimmer, Rangharajan Venkatesan, Yakun Sophia Shao, Jason Clemons, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Steve Keckler, Brucek Khailany

IEEE Journal of Solid-State Circuits (JSSC)

JSSC 2020 Best Paper award

FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning

Zhiyao Xie, Guan-Qi Fang, Yu-Hung Huang, Haoxing (Mark) Ren, Yanqing Zhang, Brucek Khailany, Shao-Yun Fang, Jiang Hu, Yiran Chen, Erick Carvajal Barboza

ASP-DAC 2020

PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network

Zhiyao Xie, Haoxing (Mark) Ren, Brucek Khailany, Ye Sheng, Santosh Santosh, Jiang Hu, Yiran Chen

ASP-DAC 2020

2019

Few-Shot Video-to-Video Synthesis

Ting-Chun Wang, Ming-Yu Liu, Andrew Tao, Guilin Liu, Jan Kautz, Bryan Catanzaro

NeurIPS

High-Quality Self-Supervised Deep Image Denoising

Samuli Laine, Tero Karras, Jaakko Lehtinen, Timo Aila

NeurIPS 2019

Dance to Music

Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz

NeurIPS

Improved Precision and Recall Metric for Assessing Generative Models

Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, Timo Aila

NeurIPS 2019

Instant Quantization of neural networks using Monte Carlo Methods

Gonçalo Mordido, Matthijs Van keirsbilck, Alex Keller

NeurIPS 2019 EMC2 workshop (IEEExplore)

Joint Optimization for Cooperative Image Captioning

Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik

International conference on computer vision (ICCV)

MAGNet: A Modular Accelerator Generator for Neural Networks

Rangharajan Venkatesan, Sophia Shao, Miaorong Wang, Jason Clemons, Steve Dai, Matt Fojtik, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Yanqing Zhang, Brian Zimmer, William Dally, Joel Emer, Steve Keckler, Brucek Khailany

International Conference On Computer Aided Design (ICCAD)

Neural Inverse Rendering of an Indoor Scene from a Single Image

Soumyadip Sengupta, Jinwei Gu, Kihwan Kim, Guilin Liu, David W. Jacobs, Jan Kautz

IEEE International Conference on Computer Vision (ICCV 2019)

Few-Shot Adaptive Gaze Estimation

Seonwook Park, Shalini De Mello, Pavlo Molchanov, Umar Iqbal, Otmar Hilliges, Jan Kautz

International Conference on Computer Vision (ICCV) 2019

Oral

Highly-scalable, Physics-informed GANs for Learning Solutions of Stochastic PDEs

Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Prabhat, George Karniadakis

PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan

IEEE International Conference of Computer Vision

Extreme View Synthesis

Inchang Choi, Orazio Gallo, Alejandro Troccoli, Min H. Kim, Jan Kautz

Neural Turtle Graphics for Modeling City Road Layouts

Hang Chu, Daiqing Li, David Acuna, Amlan Kar, Maria Shugrina, Xinkai Wei, Ming-Yu Liu, Antonio Torralba, Sanja Fidler

Meta-Sim: Learning to Generate Synthetic Datasets

Amlan Kar, Aayush Prakash, Ming-Yu Liu, Eric Cameracci, Justin Yuan, Matt Rusiniak, David Acuna, Antonio Torralba, Sanja Fidler

Confidence Regularized Self-Training

Yang Zou, Zhiding Yu, Xiaofeng Liu, B. V. K. Vijaya Kumar, Jinsong Wang

IEEE/CVF International Conference on Computer Vision (ICCV) 2019 (Oral)

Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture

Sophia Shao, Jason Clemons, Rangharajan Venkatesan, Brian Zimmer, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Brucek Khailany, Steve Keckler

International Symposium on Microarchitecture (MICRO)

Best Paper award, IEEE Micro Top Picks in Computer Architecture (Honorable Mention)

Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach.

Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna

International Symposium on Microarchitecture (MICRO)

IEEE Micro Top Picks in Computer Architecture

A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set

Clemens Eppner, Arsalan Mousavian, Dieter Fox

The International Symposium of Robotics Research (ISSR)

Video Stitching for Linear Camera Arrays

Wei-Sheng Lai, Orazio Gallo, Jinwei Gu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz

British Machine Vision Conference

GPU-Accelerated Atari Emulation for Reinforcement Learning

Steven Dalton, Iuri Frosio, Michael Garland

ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection

Saurabh Jha, Subho S. Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer

ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection

Saurabh Jha, Subho Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer

International Conference on Dependable Systems and Networks (DSN)

Semantic Image Synthesis with Spatially-Adaptive Normalization

Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu

Joint Discriminative and Generative Learning for Person Re-identification

Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang, Jan Kautz

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2019

Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera

Chao Liu, Jinwei Gu, Kihwan Kim, Srinivasa Narasimhan, Jan Kautz

IEEE CVPR 2019 (Oral)

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, Michael J. Black

IEEE CVPR 2019

STEP: Spatio-Temporal Progressive Learning for Video Action Detection

Xitong Yang, Xiaodong Yang, Ming-Yu Liu, Fanyi Xiao, Larry Davis, Jan Kautz

PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image

Chen Liu, Kihwan Kim, Jinwei Gu, Yasutaka Furukawa, Jan Kautz

IEEE CVPR 2019 (Oral)

A Style-Based Generator Architecture for Generative Adversarial Networks

Tero Karras, Samuli Laine, Timo Aila

IEEE CVPR 2019

Pixel-Adaptive Convolutional Neural Networks

Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik-Learned Miller, Jan Kautz

Computer Vision and Pattern Recognition (CVPR), 2019

Importance Estimation for Neural Network Pruning

Pavlo Molchanov, Arun Mallya, Stephen Tyree, Iuri Frosio, Jan Kautz

CVPR2019

A 0.11 pJ/Op, 0.32-128 TOPS, Scalable Multi-Chip-Module-based Deep Neural Network Accelerator with Ground-Reference Signaling in 16nm

Brian Zimmer, Rangharajan Venkatesan, Sophia Shao, Jason Clemons, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Steve Keckler, Brucek Khailany

Symposium on VLSI Circuits

DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement

Yibo Lin, Shounak Dhar, Wuxi Li, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan

Design Automation Conference (DAC) 2019

DAC 2019 Best Paper Award

High Performance Graph Convolutional Networks with Applications in Testability Analysis

Yuzhe Ma, Haoxing (Mark) Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan, Bei Yu

Analog/Mixed-Signal Hardware Error Modeling for Deep Learning Inference

Angad S. Rekhi, Brian Zimmer, Nikola Nedovic, Nigxi Liu, Rangharajan Venkatesan, Miaorong Wang, Brucek Khailany, William Dally, Tom Gray

PRIMAL: Power Inference using Machine Learning

Yuan Zhou, Haoxing (Mark) Ren, Yanqing Zhang, Ben Keller, Brucek Khailany, Zhiru Zhang

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

Esha Choukse, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Stephen W. Keckler