Research Areas

Artificial Intelligence and Machine Learning

Associated Publications

2023

Learning Autonomous Vehicle Safety Concepts from Demonstrations
Karen Leung, Sushant Veer, Edward Schmerling, Marco Pavone
American Control Conference (ACC) 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
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
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
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
Target-free Text-guided Image Manipulation
Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang
AAAI 2023
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

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
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
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, 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)
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS 2022 (oral)
NeurIPS Outstanding Paper
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion
Sheng-Yu Huang, Hao-Yu Hsu, Yu-Chiang Frank Wang
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
Demystifying Map Space Exploration for NPUs
Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna
International Symposium on Workload Characterization (IISWC)
Why are Graph Neural Networks Effective for EDA Problems?
Mark Ren, Siddhartha Nath, Yanqing Zhang, Hao Chen, Mingjie Liu
2022 International Conference on Computer-Aided Design
TransSizer: A Novel Transformer-Based Fast Gate Sizer
Siddhartha Nath, Geraldo Pradipta, Corey Hu, Tian Yang, Brucek Khailany, 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, Mark Ren
2022 International Conference on Computer-Aided Design
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
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning
Guy Tenneholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik
ICLR
XT-PRAGGMA: Crosstalk Pessimism Reduction Accessible by GPU Gate-level Simulations and Machine Learning
Vidya Chhabria, Ben Keller, Yanqing Zhang, Sandeep Vollala, Sreedhar Patty, Mark Ren, Brucek Khailany
MLCAD '22: Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD
Placement Optimization via PPA-Directed Graph Clustering
Yi-Chen Lu, Tian Yang, Sung Kyu Lim, Mark Ren
MLCAD '22: Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD
Self Adaptive Reconfigurable Arrays (SARA): Learning Flexible GEMM Accelerator Configuration and Mapping-space using ML
Ananda Samajdar, Eric Qin, Michael Pellauer, Tushar Krishna
Design Automation Conference (DAC)
Detecting Viewer-Perceived Intended Vector Sketch Connectivity
Jerry Yin, Chenxi Liu, Rebecca Liu, Nicholas Vining, Helge Rhodin, Alla Sheffer
ACM Transactions on Graphics (SIGGRAPH 2022)
Holographic Glasses for Virtual Reality
Jonghyun Kim, Manu Gopakumar, Suyeon Choi, Yifan Peng, Ward Lopes, Gordon Wetzstein
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
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller, Alex Evans, Christoph Schied, Alex Keller
ACM Transactions on Graphics (SIGGRAPH 2022)
Best Technical Paper, SIGGRAPH 2022, THE BEST INVENTIONS OF 2022, TIME
Unbiased Inverse Volume Rendering With Differential Trackers
Merlin Nimier-David, Thomas Müller, Alex Keller, Wenzel Jakob
ACM Transactions on Graphics (SIGGRAPH 2022)
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)
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
International Conference on Machine Learning (ICML), 2022
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
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
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
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
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 presentation
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
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
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
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
ACM Transactions on Graphics (SIGGRAPH 2022)
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
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, Mark Ren
2022 Design Automation Conference
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
Mark Ren, Brucek Khailany, Matt Fojtik, Yanqing Zhang
IEEE Design & Test
Learning to reason about and to act on physical cascading events
Gal Chechik, Yuval Atzmon, Eli Meirom, Shie Mannor
Arxiv

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
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
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
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
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)
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
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 presentation
One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing
Ting-Chun Wang, Arun Mallya, Ming-Yu Liu
CVPR
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 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 presentation
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, 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)
Parasitic-Aware Analog Circuit Sizing with Graph Neural Networks and Bayesian Optimization
Mingjie Liu, Walker Turner, George Kokai, David Z. Pan, Brucek Khailany, Mark Ren
2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)
MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification
Vidya A. Chhabria, Yanqing Zhang, Mark Ren, Ben Keller, Brucek Khailany, Sachin S. Sapatnekar
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
Arxiv
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
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
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)
Accelerating Reinforcement Learning through GPU Atari Emulation
Iuri Frosio, Steven Dalton
Advances in Neural Information Processing Systems 33 (NeurIPS 2020)
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
[PDF] from neurips.cc Neural ffts for universal texture image synthesis
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, 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, Mike 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
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)
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
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
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
ParaGraph: Layout Parasitics and Device Parameter Prediction using Graph Neural Networks
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, Mark Ren, Brucek Khailany
Design Automation Conference (DAC) 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
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
Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
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
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, 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)
Meshlet Priors for 3D Mesh Reconstruction
Abhishek Badki, Orazio Gallo, Jan Kautz, Pradeep Sen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020
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
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
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Mike Sullivan, Timothy Tsai, Steve Keckler
arXiv
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
arXiv
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
Arxiv
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, Mike Sullivan, Timothy Tsai, Steve Keckler
arXiv
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, 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, Mark Ren, Brucek Khailany, Ye Sheng, Santosh Santosh, Jiang Hu, Yiran Chen
ASP-DAC 2020

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
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
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 presentation
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
arXiv
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
ICCV
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)
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan
ICCV
Extreme View Synthesis
Inchang Choi, Orazio Gallo, Alejandro Troccoli, Min H. Kim, Jan Kautz
IEEE International Conference of Computer Vision
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
ICCV
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
Arxiv
ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
Saurabh Jha, Subho S. Banerjee, Timothy Tsai, Siva Hari, Mike Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer
arXiv
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)
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
Semantic Image Synthesis with Spatially-Adaptive Normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu
CVPR
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
CVPR
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
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, 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, Mark Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan, Bei Yu
Design Automation Conference (DAC)
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
Design Automation Conference (DAC)
PRIMAL: Power Inference using Machine Learning
Yuan Zhou, Mark Ren, Yanqing Zhang, Ben Keller, Brucek Khailany, Zhiru Zhang
Design Automation Conference (DAC)
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
arXiv
DeLTA: GPU Performance Model for Deep Learning Applications with In-depth Memory System Traffic Analysis
Sankug Lym, Donghyuk Lee, Niladrish Chatterjee, Mike O'Connor, Mattan Erez
International Symposium on Performance Analysis of Systems and Software (ISPASS)
Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model
Yu-Hung Huang, Zhiyao Xie, Guan-Qi Fang, Tao-Chun Yu, Mark Ren, Shao-Yun Fang, Yiran Chen, Jiang Hu
Design, Automation and Test in Europe
Timeloop: A Systematic Approach to DNN Accelerator Evaluation
Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Steve Keckler, Joel Emer
International Symposium on Performance Analysis of Systems and Software (ISPASS)
Informative Object Annotations: Tell Me Something I Don't Know
Lior Bracha, Gal Chechik
Computer Vision and Pattern Recognition
Metaoptimization on a Distributed System for Deep Reinforcement Learning
Greg Heinrich, Iuri Frosio
Unsupervised Stylish Image Description Generation via Domain Layer Norm
Cheng-Kuan Chen, Zhu-Feng Pan, Ming-Yu Liu, Min Sun
AAAI
Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz
TPAMI
A Fusion Approach for Multi-Frame Optical Flow Estimation
Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz
IEEE Winter conference of Applications of Computer Vision (WACV)

2018

Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson
Neural Information processing systems (NeurIPS)
Learning towards Minimum Hyperspherical Energy
Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
Conference on Neural Information Processing Systems (NeurIPS) 2018
Exascale Deep Learning for Climate Analytics
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
International Conference for High Performance Computing and Communications (SC'…
RouteNet: Routability Prediction for Mixed-size Designs using Convolutional Neural Network
Zhiyao Xie, Yu-Hung Huang, Guan-Qi Fang, Mark Ren, Shao-Yun Fang, Yiran Chen, Hu Jiang
International Conference On Computer Aided Design
Hand Pose Estimation via Latent 2.5 D Heatmap Regression
Umar Iqbal, Pavlo Molchanov, Thomas Breuel, Juergen Gall, Jan Kautz
ECCV2018
Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset
Qi Guo, Iuri Frosio, Orazio Gallo, Todd Zickler, Jan Kautz
ECCV 2018
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation
Zhaoyang Lv, Kihwan Kim, Alejandro Troccoli, Deqing Sun, James M. Rehg, Jan Kautz
European Conference on Computer Vision (ECCV 2018)
Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu, Fitsum A. Reda, Kevin Shih, Ting-Chun Wang, Andrew Tao, Bryan Catanzaro
ECCV
Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training
Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar, Jinsong Wang
European Conference on Computer Vision (ECCV) 2018
Switchable Temporal Propagation Network
Sifei Liu, Guangyu Zhong, Shalini De Mello, Jinwei Gu, Varun Jampani
European Conference on Computer Vision (ECCV) 2018
A Closed-form Solution to Photorealistic Image Stylization
Yijun Li, Ming-Yu Liu, Xueting Li, Ming-Hsuan Yang, Jan Kautz
ECCV
Multimodal Unsupervised Image-to-Image Translation
Xun Huang, Ming-Yu Liu, Serge Belongie, Jan Kautz
ECCV
Superpixel Sampling Networks
Varun Jampani, Deqing Sun, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz
European Conference on Computer Vision (ECCV), 2018
Machine Learning and Rendering
Alex Keller, Jaroslav Křivánek, Jan Novák, Anton Kaplanyan, Marco Salvi
ACM SIGGRAPH 2018 Courses
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila
Proc. ICML 2018
Light-weight Head Pose Invariant Gaze Tracking
Rajeev Ranjan, Shalini De Mello, Jan Kautz
IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) 2018
Best Paper (runner up) Workshop on Analysis and Modeling of Faces and Gestures
MoCoGAN: Decomposing Motion and Content for Video Generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, Jan Kautz
CVPR
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger, Pavlo Molchanov, Jan Kautz, Sina Honari
Conference on Computer Vision and Pattern Recognition
Improving Landmark Localization with Semi-Supervised Learning
Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Pal, Jan Kautz
CVPR
Making Convolutional Networks Recurrent for Visual Sequence Learning
Xiaodong Yang, Pavlo Molchanov, Jan Kautz
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Learning Strict Identity Mappings in Deep Residual Networks
Xin Yu, Zhiding Yu, Srikumar Ramalingam
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2018
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz
CVPR
SPLATNet: Sparse Lattice Networks for Point Cloud Processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, Jan Kautz
CVPR 2018 (oral)
Deep Semantic Face Deblurring
Ziyi Shen, Wei-Sheng Lai, Tingfa Xu, Jan Kautz, Ming-Hsuan Yang
IEEE Computer Vision and Pattern Recognition (CVPR)
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, Bryan Catanzaro
CVPR
Decoupled Networks
Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2018
Geometry-Aware Learning of Maps for Camera Localization
Samarth Brahmbhatt, Jinwei Gu, Kihwan Kim, James Hays, Jan Kautz
CVPR 2018 (Spotlight)
UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition
Kartik Hegde, Jiyong Yu, Rohit Agrawal, Mengjia Yan, Michael Pellauer, Christopher W. Fletcher
International Symposium on Computer Architecture (ISCA)
Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training
Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Steve Keckler, Yuan Xie
arXiv
Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning
Yuval Atzmon, Gal Chechik
The conference on uncertainty in artificial intelligence (UAI 2018)
Reblur2Deblur: Deblurring Videos via Self-Supervised Learning
Huaijin Chen, Jinwei Gu, Orazio Gallo, Ming-Yu Liu, Ashok Veeraraghavan, Jan Kautz
IEEE International Conference on Computational Photography (ICCP)
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras, Timo Aila, Samuli Laine, Jaakko Lehtinen
ICLR 2018
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
Sam Leroux, Pavlo Molchanov, Pieter Simoens, Bart Dhoedt, Thomas Breuel, Jan Kautz
International Conference on Learning Representations, Workshop
Synchronous Multi-GPU Deep Learning with Low-Precision Communication: An Experimental Study
Demjan Grubic, Leo Tam, Dan Alistarh, Ce Zhang
EDBT 2018
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks
Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Youngeun Kwon, Steve Keckler
International Symposium on High Performance Computer Architecture (HPCA)
Stitch-X: An Accelerator Architecture for Exploiting Unstructured Sparsity in Deep Neural Networks
Ching-En Lee, Yakun Sophia Shao, Jie-Fang Zhang, Angshuman Parashar, Joel Emer, Steve Keckler, Zhengya Zhang
SysML Conference
Learning Binary Residual Representations for Domain-specific Video Streaming
Yi-Hsuan Tsai, Ming-Yu Liu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz
AAAI
Learning Adaptive Parameter Tuning for Image Processing
Jingming Dong, Iuri Frosio, Jan Kautz
Electronic Imaging 2018, Image Processing: Algorithms and Systems XVI, Burlinga…

2017

Parallel Complexity of Forward and Backward Propagation
Maxim Naumov
arXiv:1712.06577 [cs.LG]
Machine Learning and Integral Equations
Ken Dahm, Alex Keller
Machine Learning and Integral Equations
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
Aditya Devarakonda, Maxim Naumov, Michael Garland
arXiv:1712.02029 [cs.LG]
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu, Thomas Breuel, Jan Kautz
NIPS
Learning Affinity via Spatial Propagation Networks
Sifei Liu, Shalini De Mello, Jinwei Gu, Guangyu Zhong, Ming-Hsuan Yang, Jan Kautz
Conference on Neural Information Processing Systems (NIPS) 2017
Parallel Jaccard and Related Graph Clustering Techniques
Alexandre Fender, Nahid Emad, Serge Petiton, Joe Eaton, Maxim Naumov
Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for L…
Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications
Guanpeng Li, Siva Hari, Michael B. Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel Emer, Steve Keckler
The International Conference for High Performance Computing, Networking, Storag…
Learning to Super-Resolve Blurry Face and Text Images
Xiangyu Xu, Deqing Sun, Jinshan Pan, Yujin Zhang, Hanspeter Pfister, Ming-Hsuan Yang
International Conference on Computer Vision
A Lightweight Approach for On-the-Fly Reflectance Estimation
Kihwan Kim, Jinwei Gu, Stephen Tyree, Pavlo Molchanov, Matthias Nießner, Jan Kautz
IEEE International Conference on Computer Vision (ICCV 2017)
Group online adaptive learning
Alon Zweig, Gal Chechik
Journal Machine Learning
Feedforward and Recurrent Neural Networks Backward Propagation and Hessian in Matrix Form
Maxim Naumov
arXiv:1709.06080 [cs.LG]
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao , Meng-Li Shi, Ming-Yu Liu, Min Sun
IJCAI
Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion
Tero Karras, Timo Aila, Samuli Laine, Antti Herva, Jaakko Lehtinen
SIGGRAPH 2017
Parallel Modularity Clustering
Alexandre Fender, Nahid Emad, Serge Petiton, Maxim Naumov
Procedia Computer Science (Elsevier)
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks
Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel Emer, Steve Keckler, William Dally
arXiv
Pruning Convolutional Neural Networks for Resource Efficient Inference
Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, Jan Kautz
International Conference on Learning Representations (ICLR 2017)
Context-aware Captions from Context-agnostic Supervision
Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik
Computer Vision and Pattern Recognition
Learning From Noisy Large-Scale Datasets With Minimal Supervision
Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge Belongie
Computer Vision and Pattern Recognition
Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU
Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz, Mohammad Babaeizadeh
Proceeding of ICLR 2017
Loss Functions for Image Restoration with Neural Networks
Hang Zhao, Orazio Gallo, Iuri Frosio, Jan Kautz
IEEE Transactions on Computational Imaging

2016

Tensor Contractions with Extended BLAS Kernels on CPU and GPU
Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka
2016 IEEE 23rd International Conference on High Performance Computing (HiPC)
Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU
Mohammad Babaeizadeh, Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz
arXiv
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design.
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
International Symposium on Microarchitecture (MICRO)
Temporal Ensembling for Semi-Supervised Learning
Samuli Laine, Timo Aila
ICLR 2017
Multilayer and Multimodal Fusion of Deep Neural Networks for Video Classification
Xiaodong Yang, Pavlo Molchanov, Jan Kautz
ACM Multimedia
Towards Selecting Robust Hand Gestures for Automotive Interfaces
Shalini Gupta, Pavlo Molchanov, Xiaodong Yang, Stephen Tyree, Jan Kautz
IEEE Intelligent Vehicles Symposium (IV) 2016
Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks
Yu-Hsin Chen, Joel Emer, Vivienne Sze
International Symposium on Computer Architecture (ISCA)
Online Detection and Classification of Dynamic Hand Gestures with Recurrent 3D Convolutional Neural Networks
Pavlo Molchanov, Xiaodong Yang, Shaline Gupta, Kihwan Kim, Stephen Tyree, Jan Kautz
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016
Parallel Spectral Graph Partitioning
Maxim Naumov, Timothy Moon
Technical Report NVR-2016-001
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
arXiv

2015

Compressing Neural Networks with the Hashing Trick
Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen
Proceedings of The 32nd International Conference on Machine Learning
Hand Gesture Recognition with 3D Convolutional Neural Networks
Pavlo Molchanov, Shalini Gupta, Kihwan Kim, Jan Kautz
IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) 2015
Winner (1st place) Hand Gesture Recognition Challenge
Multi-sensor System for Driver’s Hand-Gesture Recognition
Pavlo Molchanov, Shalini Gupta, Kihwan Kim, Kari Pulli
IEEE International Conference on Automatic Face and Gesture Recognition (FG) 20…
Short-Range FMCW Monopulse Radar for Hand-Gesture Sensing
Pavlo Molchanov, Shalini Gupta, Kihwan Kim, Kari Pulli
IEEE International Radar Conference
Adaptive Segmentation based on a Learned Quality Metric
Iuri Frosio, Ed Ratner
Proceedings of the 10th International Conference on Computer Vision Theory and …
Machine Learning for Adaptive Bilateral Filtering
Iuri Frosio, Karen Egiazarian, Kari Pulli
Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII

2014

cuDNN: Efficient Primitives for Deep Learning
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer
Deep Learning and Representation Learning Workshop (NIPS2014)

Researchers

Aamer Jaleel
Aaron Lefohn
Ajay Mandlekar
Alex Keller
Ali Hatamizadeh
Andrei Alexandrescu
Andriy Myronenko
Angshuman Parashar
Animesh Garg
Anthony Agnesina
Apoorva Sharma
Arash Vahdat
Balakumar Sundaralingam
Bart Wronski
Benjamin Eckart
Benjamin Klenk
Boris Ivanovic
Boyi Li
Brucek Khailany
Caelan Garrett
Can Zhao
Charbel Sakr
Chen Tessler
Chen-Hsuan Lin
Chia-Tung (Mark) Ho
Chien-Yi Wang
Christoph Schied
Claudia Pérez D’Arpino
Clemens Eppner
Craig Kolb
Cris Cecka
Daguang Xu
David Nellans
De-An Huang
Dennis Abts
Dieter Fox
Dong Yang
Evgeny Bolotin
Fabrice Rousselle
Fayçal Aït Aoudia
Frank Wang
Gal Chechik
Gal Dalal
Guilin Liu
Hang Su
Haoyu Yang
Heng Yang
Holger Roth
Hongxu Danny Yin
Iuri Frosio
Jacob Munkberg
Jaideep Pathak
Jakob Hoydis
Jan Kautz
Jan Novák
Jeff Smith
Jiaming Song
Jie Xu
Linxi "Jim" Fan
Joohwan Kim
Josef Spjut
Kaichun Mo
Kamyar Azizzadenesheli
Koki Nagano
Li Xu
Marco Salvi
Mark Ren
Markus Kettunen
Merlin Nimier-David
Michael Stengel
Miika Aittala
Mike O'Connor
Mike Pritchard
Min-Hung Chen
Ming-Yu Liu
Mingjie Liu
Morteza Mardani
Nathaniel Pinckney
Nicolai Oswald
Nikola Kovachki
Nikolaus Binder
Niladrish Chatterjee
Noah Brenowitz
Onni Kosomaa
Orazio Gallo
Pavlo Molchanov
Peter Karkus
Petrik Clarberg
Qijing Jenny Huang
Rachel Brown
Rama Akkiraju
Rowland O'Flaherty
Samuli Laine
Saurav Muralidharan
Sebastian Cammerer
Seungjun Nah
Shalini De Mello
Shiyi Lan
Siddharth Gururani
Sifei Liu
Simon Kallweit
Siva Hari
Song Han
Stephen Tyree
Steve Keckler
Szu-Wei Fu
Taylor Patti
Thomas Müller
Timo Aila
Ting-Chun Wang
Tucker Hermans
Umar Iqbal
Valts Blukis
Vinu Joseph
Vishwesh Nath
Wei Yang
Wen-mei Hwu
William Dally
Ye Yuan
Yijie Guo
Yogesh Balaji
Yu-Wei Chao
Yue Wang
Yufan He
Zhiding Yu
Ziyue Xu