Publications

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

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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
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
Placement Optimization via PPA-Directed Graph Clustering
Yi-Chen Lu, Tian Yang, Sung Kyu Lim, Haoxing (Mark) Ren
GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access
Daniel Schäufele, Guillermo Marcus, Nikolaus Binder, Matthias Mehlhose, Alex Keller, Slawomir Stańczak
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
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
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
Top 25%
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller, Alex Evans, Christoph Schied, Alex Keller
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
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Brucek Khailany, William Dally
Adaptive Neural Network-based OFDM Receivers
Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer, Takayuki Shimizu, Hongsheng Lu, Stephan ten Brink
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
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
Correcting Robot Plans with Natural Language Feedback
Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis, Chris Paxton, Tucker Hermans, Antonio Torralba, Jacob Andreas, Dieter Fox
Whose Track Is It Anyway? Improving Robustness to Tracking Errors with Affinity-Based Prediction
Xinshuo Weng, Boris Ivanovic, Kris Kitani, Marco Pavone
ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning
Yuxiao Chen, Boris Ivanovic, Marco Pavone
Polymorphic-GAN: Generating Aligned Samples across Multiple Domains with Learned Morph Maps
Seung Wook Kim, Karsten Kreis, Daiqing Li, Antonio Torralba, Sanja Fidler
GroupViT: Semantic Segmentation Emerges from Text Supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, Xiaolong Wang
FreeSOLO: Learning to Segment Objects without Annotations
Xinlong Wang, Zhiding Yu, Shalini De Mello, Jan Kautz, Anima Anandkumar, Chunhua Shen, Jose M. Alvarez
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
Oral
BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations
Daiqing Li, Huan Ling, Seung Wook Kim, Karsten Kreis, Adela Barriuso, Sanja Fidler, Antonio Torralba
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
Optimizing tensor network contraction using reinforcement learning
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik
Injecting Planning-Awareness into Prediction and Detection Evaluation
Boris Ivanovic, Marco Pavone
MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
Xinshuo Weng, Boris Ivanovic, Marco Pavone
Propagating State Uncertainty Through Trajectory Forecasting
Boris Ivanovic, Yifeng Lin, Shubham Shrivastava, Punarjay Chakravarty, Marco Pavone
MatBuilder: Mastering Sampling Uniformity Over Projections
Loïs Paulin, Nicolas Bonneel, David Coeurjolly, Jean-Claude Iehl, Alex Keller, Victor Ostromoukhov
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
Rinon Gal, Or Patashnik, Haggai Maron, Amir Bermano, Gal Chechik, Daniel Cohen-Or
Accelerated Policy Learning with Parallel Differentiable Simulation
Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin