Publications

Our publications provide insight into some of our leading-edge research.

Filters

Filters

Publication Year

Research Areas

Events

2023

Joint Neural Denoising of Surfaces and Volumes
Nikolai Hofmann, Jon Hasselgren, Jacob Munkberg
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence
Michael Bauer, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, Alex Aiken
Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows
Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Haoxing (Mark) Ren
Beyond CPO: A Motivation and Approach for Bringing Optics onto the Silicon Interposer
Ben Lee, Nikola Nedovic, Trey Greer, Tom Gray
Target-free Text-guided Image Manipulation
Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavy, Gal Dalal
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
BufFormer: A Generative ML Framework for Scalable Buffering
Rongjian Liang, Siddhartha Nath, Anand Rajaram, Jiang Hu, Haoxing (Mark) Ren
Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System
Rachel Brown, Vasha DuTell, Bruce Walter, Ruth Rosenholtz, Peter Shirley, Morgan McGuire, David Luebke
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning
Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler
Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
Cheng-Yen Hsieh, Chih-Jung Chang, Fu-En Yang, Frank Wang

2022

Planning Visual-Tactile Precision Grasps via Complementary Use of Vision and Touch
Martin Matak, Tucker Hermans
Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation
Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, Dieter Fox
Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
Alec Farid, Sushant Veer, Boris Ivanovic, Karen Leung, Marco Pavone
DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles
Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone
Robust Trajectory Prediction against Adversarial Attacks
Yulong Cao, Danfei Xu, Xinshuo Weng, Z. Morely Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone
Selected for Oral Presentation
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
Yann Labbe, Lucas Manuelli, Arsalan Mousavian, Stephen Tyree, Stan Birchfield, Jonathan Tremblay, et al.
Learning Joint Detection, Equalization and Decoding for Short-Packet Communications
Sebastian Dörner, Jannis Clausius, Sebastian Cammerer, Stephan ten Brink
QuadStream: A Quad-Based Scene Streaming Architecture for Novel Viewpoint Reconstruction
Jozef Hladky, Michael Stengel, Nicholas Vining, Bernhard Kerbl, Hans-Peter Seidel, Markus Steinberger
Efficient Arithmetic Block Identification with Graph Learning and Network-flow
Ziyi Wang, Zhuolun He, Chen Bai, Haoyu Yang, Bei Yu
Display Size and Targeting Performance: Small Hurts, Large May Help
Joohwan Kim, Arjun Madhusudan, Benjamin Watson, Ben Boudaoud, Roland Tarrazo, Josef Spjut
Deep Learning-Based Synchronization for Uplink NB-IoT
Fayçal Aït Aoudia , Jakob Hoydis, Sebastian Cammerer, Matthijs Van keirsbilck, Alex Keller
Graph Neural Networks for Channel Decoding
Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia , Alex Keller
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Jiaqi Gu, Ben Keller, Jean Kossaifi, Anima Anandkumar, Brucek Khailany, David Z. Pan
Spotlight Paper
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
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
Motion Policy Networks
Adam Fishman, Adithya Murali, Clemens Eppner, Bryan Peele, Byron Boots, Dieter Fox
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Eli Meirom, Gal Chechik, Yuval Atzmon
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS Outstanding Paper