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NVIDIA at NeurIPS 2022

Nov 28-Dec 9, 2022 
Nov. 28 - Dec  2: New Orleans Convention Center
Dec 5-9: Digital Event

At the forefront of AI innovation, NVIDIA continues to push the boundaries of technology in machine learning, self-driving cars, robotics, graphics, simulation and more. NVIDIA researchers will present groundbreaking papers at NeurIPS from November 28 to December 9. Join us to see the latest advancements in research.

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Presentations

Our accepted papers feature a range of groundbreaking research. From alias-free general adversarial networks (GANs) that create photorealistic images to semantic segmentation with transformers, explore the exceptional work we’re bringing to the NeurIPS community.

  • Papers
  • Posters
  • Workshops

Winner of Outstanding Main Track Papers Award

Elucidating the Design Space of Diffusion-Based Generative Models

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine | Paper

Winner of Outstanding Datasets and Benchmarks Papers Award

MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge

Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar | Paper

GET3D: A Generative Model of High-Quality 3D Textured Shapes Learned from Images

Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler | Paper 

Shape, Light, and Material Decomposition from Images Using Monte Carlo Rendering and Denoising (3D MoMa +)

Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg | Paper

Implicit Warping for Animation with Image Sets

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

PeRFception: Perception Using Radiance Fields

Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Chris Choy, Anima Anandkumar, Minsu Cho, Jaesik Park | Paper

LION: Latent Point Diffusion Models for 3D Shape Generation

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

Denoising Diffusion Restoration Models

Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song | Paper

Breaking Bad: A Dataset for Geometric Fracture and Reassembly

Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson | Paper

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models            

Manli Shu, Chaowei Xiao, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar | Paper

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models

Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro | Paper

Generating Long Videos of Dynamic Scenes

Tim Brooks, Janne Hellsten, Miika Aittala, Ting-Chun Wang, Timo Aila, Jaakko Lehtinen, Ming-Yu Liu, Alexei Efros, Tero Karras | Paper

SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments

Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg | Paper

MoCoDA: Model-Based Counterfactual Data Augmentation

Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg | Paper

Implicit Neural Representations with Levels of Experts

Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu | Paper

Learning Dissipative Dynamics in Chaotic Systems

Zongyi Li, Miguel Liu-Schiaffini, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar | Paper

MinVIS: A Minimal Video Instance Segmentation Framework Without Video-Based Training

De-An Huang, Zhiding Yu, Anima Anandkumar | Paper

Pretrained Language Models for Interactive Decision-Making

Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu | Paper

Optimizing Data Collection for Machine Learning

Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc Law | Paper

GENIE: Higher-Order Denoising Diffusion Solvers

Tim Dockhorn, Arash Vahdat, Karsten Kreis | Paper

Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits

Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar | Paper

Elucidating the Design Space of Diffusion-Based Generative Models

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine | Paper  

Structural Pruning via Latency-Saliency Knapsack

Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez | Paper

Embodied Scene-Aware Human Pose Estimation

Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani | Paper

Concrete Score Matching: Generalized Score Matching for Discrete Data

Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon | Paper

LISA: Learning Interpretable Skill Abstractions from Language

Divyansh Garg, Sakanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon | Paper

Batch Bayesian Optimisation via Density-Ratio Estimation with Guarantees

Rafael Oliveira, Louis Tiao, Fabio Ramos | Paper

Reinforcement Learning with a Terminator

Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal | Paper

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron | Paper

Paraphrasing Is All You Need for Novel Object Captioning

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

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

Sheng Yu Huang, Hao-Yu Hsu, Frank Wang | Paper

Tractable Optimality in Episodic Latent MABs

J. Kwon, Y. Efroni, C. Caramanis, S. Mannor | Paper

Uncertainty Estimation Using Riemannian Model Dynamics

Guy Tennenholtz · Shie Mannor | Paper

Efficient Risk-Averse Reinforcement Learning

Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor | Paper

Finite Sample Analysis of Dynamic Regression Parameter Learning      

Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer | Paper

Factuality-Enhanced Language Models for Open-Ended Text Generation

Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro | Paper

Trustworthy and Socially Responsible Machine Learning

Huan Zhang, Linyi Li, Chaowei Xiao, J. Zico Kolter, Anima Anandkumar, Bo Li | Paper

Machine Learning and the Physical Sciences

Atilim Gunes Baydin, Adji Bousso Dieng, Emine Kucukbenli, Gilles Louppe, Siddharth Mishra-Sharma, Benjamin Nachman, Brian Nord, Savannah Thais, Anima Anandkumar, Kyle Cranmer, Lenka Zdeborová | Paper

First Workshop on Interpolation Regularizers and Beyond

Yann Dauphin, David Lopez-Paz, Vikas Verma, Boyi Li | Paper

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

Mingjie Liu, Haoyu Yang, David Z. Pan, Brucek Khailany, Haoxing Ren | Paper

Multi-Objective Reinforcement Learning with Adaptive Pareto Reset for Prefix Adder Design

Jialin Song, Rajarshi Roy, Jonathan Raiman, Robert Kirby, Neel Kant, Saad Godil, Bryan Catanzaro | Coming Soon

Implementing Reinforcement Learning Data Center Congestion Control in NVIDIA NICs

Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal | Paper

VIMA: General Robot Manipulation with Multimodal Prompts

Yunfan Jiang, Agrim Gupta*, Zichen Zhang*, Guanzhi Wang*, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, Linxi Fan | Paper

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

Boris Ivanovic, James Harrison, Marco Pavone | Paper

Machine Learning Methods Applied to Cortico-Cortical Evoked Potentials Aid in Localizing Seizure Onset Zones

Ian Malone, Kaleb Smith*, Morgan Urdaneta, Christopher Butson, John Rolston | Paper

Robust Trajectory Prediction Against Adversarial Attacks

Yulong Cao, Danfei Xu, Xinshuo Weng, Zhuoqing Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone | Paper

AdvDO: Realistic Adversarial Attacks for Trajectory Prediction

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

JPEG Artifact Correction Using Denoising Diffusion Restoration Models   

Bahjat Kawar, Jiaming Song, Stefano Ermon, Michael Elad | Paper

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

Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner, Adam Fishman, Dieter Fox | Paper

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression

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

AI for Science: Progress and Promises

Yi Ding, Yuanqi Du, Tianfan Fu, Hanchen Wang, Anima Anandkumar, Yoshua Bengio, Anthony Gitter, Carla Gomes, Aviv Regev, Max Welling, Marinka Zitnik | Paper

NeurIPS 2022 Workshop on Score-Based Methods

Yingzhen Li, Yang Song, Valentin De Bortoli, Francois-Xavier Briol, Wenbo Gong, Alexia Jolicoeur-Martineau, Arash Vahdat | Paper

NVIDIA FLARE: Federated Learning from Simulation to Real World

Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang, Ziyue Xu, Yuan-Ting Hsieh, Kristopher Kersten, Ahmed Harouni, Can Zhao, Kevin Lu, Zhihong Zhang, Wenqi Li, Andriy Myronenko, Dong Yang, Sean Yang, Nicola Rieke, Abood Quraini, Chester Chen, Daguang Xu, Nic Ma, Prerna Dogra, Mona Flores, Andrew Feng | Paper

FO-PINNs: A First-Order Formulation for Physics-Informed Neural Networks

Rini Gladstone, Mohammad Amin Nabian, Hadi Meidani | Paper

Calibration of Large Neural Weather Models

Andre Graubner, Morteza Mardani, Jaideep Pathak, Karthik Kashinath, Mike Pritchard, Kamyar Azizzadensheli, Anima Anandkumar | Paper

FALCON: Fourier Adaptive Learning and Control for Disturbance Rejection Under Extreme Turbulence

Sahin Lale, Peter I Renn, Kamyar Azizzadenesheli, Babak Hassibi, Morteza Gharib, Anima Anandkumar | Paper

Fast Sampling of Diffusion Models via Operator Learning

Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar | Paper

Generalized Laplacian Positional Encoding for Graph Representation Learning

Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron | Paper

Conformal Semantic Keypoint Detection with Statistical Guarantees

Heng Yang, Marco Pavone | Paper

DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone | Paper

Foundation Models for Semantic Novelty in Reinforcement Learning

Tarun Gupta, Peter Karkus, Tong Che, Danfei Xu, Marco Pavone | Paper

Insights Towards Sim2Real Contact-Rich Manipulation

Michael Noseworthy, Iretiayo Akinola, Yashraj Narang, Fabio Ramos, Lucas Manuelli, Ankur Handa, Dieter Fox | Paper

SoftTreeMax: Policy Gradient with Tree Search

Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik | Paper

Show More
Show Less

Shape, Light, and Material Decomposition from Images Using Monte Carlo Rendering and Denoising (3D MoMa +)

Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg | Poster

LION: Latent Point Diffusion Models for 3D Shape Generation

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

Denoising Diffusion Restoration Models

Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song | Poster

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Manli Shu, Chaowei Xiao, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar | Poster

Implicit Neural Representations with Levels of Experts

Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu | Coming Soon

Generating Long Videos of Dynamic Scenes

Tim Brooks, Janne Hellsten, Miika Aittala, Ting-Chun Wang, Timo Aila, Jaakko Lehtinen, Ming-Yu Liu, Alexei Efros, Tero Karras | Poster

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models

Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro | Poster

MoCoDA: Model-Based Counterfactual Data Augmentation               

Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg | Poster

Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits

Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar | Poster

Pretrained Language Models for Interactive Decision-Making

Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu | Poster

Learning Dissipative Dynamics in Chaotic Systems

Zongyi Li, Miguel Liu-Schiaffini, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar | Poster

MinVIS: A Minimal Video Instance Segmentation Framework Without Video-based Training

De-An Huang, Zhiding Yu, Anima Anandkumar | Poster

Optimizing Data Collection for Machine Learning

Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc Law | Poster

GENIE: Higher-Order Denoising Diffusion Solvers

Tim Dockhorn, Arash Vahdat, Karsten Kreis | Poster

Elucidating the Design Space of Diffusion-Based Generative Models               

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine | Poster

Structural Pruning via Latency-Saliency Knapsack

Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez | Poster

Embodied Scene-Aware Human Pose Estimation

Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani | Poster

Concrete Score Matching: Generalized Score Matching for Discrete Data

Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon | Poster

LISA: Learning Interpretable Skill Abstractions from Language

Divyansh Garg, Sakanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon | Poster

Batch Bayesian Optimisation via Density-Ratio Estimation with Guarantees

Rafael Oliveira, Louis Tiao, Fabio Ramos | Poster

Reinforcement Learning with a Terminator

Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal | Poster

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron | Poster

Paraphrasing Is All You Need for Novel Object Captioning

Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Russ Salakhutdinov, Louis-Philippe Morency, Frank Wang | Coming Soon

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

Sheng Yu Huang, Hao-Yu Hsu, Frank Wang | Coming Soon

Tractable Optimality in Episodic Latent MABs

J. Kwon, Y. Efroni, C. Caramanis, S. Mannor | Poster

Uncertainty Estimation Using Riemannian Model Dynamics

Guy Tennenholtz, Shie Mannor | Coming Soon

Efficient Risk-Averse Reinforcement Learning

Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor | Poster

Finite Sample Analysis of Dynamic Regression Parameter Learning

Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer | Coming Soon

FO-PINNs: A First-Order Formulation for Physics-Informed Neural Networks

Rini Gladstone, Mohammad Amin Nabian, Hadi Meidani | Poster

Calibration of Large Neural Weather Models

Andre Graubner, Morteza Mardani, Jaideep Pathak, Karthik Kashinath, Mike Pritchard, Kamyar Azizzadensheli, Anima Anandkumar | Poster

FALCON: Fourier Adaptive Learning and Control for Disturbance Rejection Under Extreme Turbulence

Sahin Lale, Peter I Renn, Kamyar Azizzadenesheli, Babak Hassibi, Morteza Gharib, Anima Anandkumar | Poster

Fast Sampling of Diffusion Models via Operator Learning

Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar | Poster
Show More
Show Less

Trustworthy and Socially Responsible Machine Learning

Huan Zhang, Linyi Li, Chaowei Xiao, J. Zico Kolter, Anima Anandkumar, Bo Li | Workshop

Machine Learning and the Physical Sciences

Atilim Gunes Baydin, Adji Bousso Dieng, Emine Kucukbenli, Gilles Louppe, Siddharth Mishra-Sharma, Benjamin Nachman, Brian Nord, Savannah Thais, Anima Anandkumar, Kyle Cranmer, Lenka Zdeborová | Workshop

First Workshop on Interpolation Regularizers and Beyond

Yann Dauphin, David Lopez-Paz, Vikas Verma, Boyi Li | Workshop

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

Mingjie Liu, Haoyu Yang, David Z. Pan, Brucek Khailany, Haoxing Ren | Coming Soon

Multi-Objective Reinforcement Learning with Adaptive Pareto Reset for Prefix Adder Design

Jialin Song, Rajarshi Roy, Jonathan Raiman, Robert Kirby, Neel Kant, Saad Godil, Bryan Catanzaro | Workshop

Implementing Reinforcement Learning Data Center Congestion Control in NVIDIA NICs

Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal | Workshop

VIMA: General Robot Manipulation with Multimodal Prompts

Yunfan Jiang, Agrim Gupta*, Zichen Zhang*, Guanzhi Wang*, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, Linxi Fan | Workshop

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

Boris Ivanovic, James Harrison, Marco Pavone | Workshop

Disaster Risk Monitoring Using Satellite Imagery               

Kevin Lee, Siddha Ganju | Workshop

Machine Learning Methods Applied to Cortico-Cortical Evoked Potentials Aid in Localizing Seizure Onset Zones

Ian Malone, Kaleb Smith*, Morgan Urdaneta, Christopher Butson, John Rolston | Workshop

Robust Trajectory Prediction Against Adversarial Attacks

Yulong Cao, Danfei Xu, Xinshuo Weng, Zhuoqing Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone | Workshop Poster

AdvDO: Realistic Adversarial Attacks for Trajectory Prediction

Yulong Cao, Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone | Workshop Poster

JPEG Artifact Correction Using Denoising Diffusion Restoration Models

Bahjat Kawar, Jiaming Song, Stefano Ermon, Michael Elad | Workshop

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

Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner,  Adam Fishman, Dieter Fox | Workshop Paper

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression

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

Generalized Laplacian Positional Encoding for Graph Representation Learning               

Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron | Workshop Poster

Conformal Semantic Keypoint Detection with Statistical Guarantees

Heng Yang, Marco Pavone | Workshop

DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone | Workshop

Foundation Models for Semantic Novelty in Reinforcement Learning

Tarun Gupta, Peter Karkus, Tong Che, Danfei Xu, Marco Pavone | Workshop

Insights Towards Sim2Real Contact-Rich Manipulation

Michael Noseworthy, Iretiayo Akinola, Yashraj Narang, Fabio Ramos, Lucas Manuelli, Ankur Handa, Dieter Fox | Workshop Paper

SoftTreeMax: Policy Gradient with Tree Search

Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik | Workshop
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