Anandkumar, Anima

167 publications

CVPR 2025 A Unified Model for Compressed Sensing MRI Across Undersampling Patterns Armeet Singh Jatyani, Jiayun Wang, Aditi Chandrashekar, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

ICLR 2025 Diffusion State-Guided Projected Gradient for Inverse Problems Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar

TMLR 2025 Enabling Automatic Differentiation with Mollified Graph Neural Operators Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

NeurIPS 2025 Guided Diffusion Sampling on Function Spaces with Applications to PDEs Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar

CVPR 2025 Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing Bingliang Zhang, Wenda Chu, Julius Berner, Chenlin Meng, Anima Anandkumar, Yang Song

ICLR 2025 LeanAgent: Lifelong Learning for Formal Theorem Proving Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar

TMLR 2025 LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction Robert Joseph George, Suozhi Huang, Peiyang Song, Anima Anandkumar

ICLRW 2025 LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction Suozhi Huang, Peiyang Song, Robert Joseph George, Anima Anandkumar

NeurIPS 2025 NOBLE - Neural Operator with Biologically-Informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams, Philip H. Wong, Costas A. Anastassiou, Anima Anandkumar

UAI 2025 Off-Policy Predictive Control with Causal Sensitivity Analysis Myrl G Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar

NeurIPS 2025 R-KV: Redundancy-Aware KV Cache Compression for Reasoning Models Zefan Cai, Wen Xiao, Hanshi Sun, Cheng Luo, Yikai Zhang, Ke Wan, Yucheng Li, Yeyang Zhou, Li-Wen Chang, Jiuxiang Gu, Zhen Dong, Anima Anandkumar, Abedelkadir Asi, Junjie Hu

ICLR 2025 Robust Representation Consistency Model via Contrastive Denoising Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar

JMLR 2025 Score-Based Diffusion Models in Function Space Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista, Christopher Beckham, Kamyar Azizzadenesheli, Jean Kossaifi, Vikram Voleti, Jiaming Song, Karsten Kreis, Jan Kautz, Christopher Pal, Arash Vahdat, Anima Anandkumar

ICLR 2025 Sequential Controlled Langevin Diffusions Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar

ICLR 2025 T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar

NeurIPSW 2024 A Foundational Multi-Modal Knowledge Graph for Pancreatic Cancer Drug Effects Prediction Jingwen Hui, Shengchao Liu, Xiaohua Huang, Anima Anandkumar

NeurIPSW 2024 A Geometric Foundation Model for Crystalline Material Discovery Shengchao Liu, Liang Yan, Weitao Du, Zhuoxinran Li, Zhiling Zheng, Omar M. Yaghi, Christian Borgs, Hongyu Guo, Anima Anandkumar, Jennifer T Chayes

ICLRW 2024 A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh C Bhethanabotla, Nakul Rampal, Omar M. Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T Chayes

ICMLW 2024 An Equivariant Flow Matching Framework for Learning Molecular Crystallization Shengchao Liu, Liang Yan, Hongyu Guo, Anima Anandkumar

ICML 2024 Autoformalizing Euclidean Geometry Logan Murphy, Kaiyu Yang, Jialiang Sun, Zhaoyu Li, Anima Anandkumar, Xujie Si

NeurIPSW 2024 Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators Chuwei Wang, Julius Berner, Zongyi Li, Di Zhou, Jiayun Wang, Jane Bae, Anima Anandkumar

NeurIPS 2024 CARE: A Benchmark Suite for the Classification and Retrieval of Enzymes Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Anima Anandkumar, Frances H. Arnold, Yisong Yue

TMLR 2024 Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar

ICML 2024 DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu

NeurIPS 2024 Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Anima Anandkumar, Furong Huang

ICLR 2024 Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar

ICML 2024 Equivariant Graph Neural Operator for Modeling 3D Dynamics Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar

ICLR 2024 Eureka: Human-Level Reward Design via Coding Large Language Models Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar

TMLR 2024 Fast Training of Diffusion Models with Masked Transformers Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar

ICMLW 2024 Fourier Neural Operator Based Surrogates for $\textrm{CO}_2$ Storage in Realistic Geologies Anirban Chandra, Marius Koch, Suraj Pawar, Aniruddha Panda, Kamyar Azizzadenesheli, Jeroen Snippe, Faruk O. Alpak, Farah Hariri, Clement Etienam, Pandu Devarakota, Anima Anandkumar, Detlef Hohl

ICML 2024 GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

ICLRW 2024 GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

ICMLW 2024 Geometry Aware Deep Learning for Integrated Closed-Shell and Open-Shell Systems Beom Seok Kang, Vignesh C Bhethanabotla, Mohammadamin Tavakoli, William Goddard, Anima Anandkumar

NeurIPSW 2024 Geometry-Text Multi-Modal Foundation Model for Reactivity-Oriented Molecule Editing Haorui Li, Shengchao Liu, Hongyu Guo, Anima Anandkumar

ICLR 2024 Guaranteed Approximation Bounds for Mixed-Precision Neural Operators Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar

CVPR 2024 Improving Distant 3D Object Detection Using 2D Box Supervision Zetong Yang, Zhiding Yu, Chris Choy, Renhao Wang, Anima Anandkumar, Jose M. Alvarez

TMLR 2024 Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs Robert Joseph George, Jiawei Zhao, Jean Kossaifi, Zongyi Li, Anima Anandkumar

NeurIPSW 2024 Language Models for Text-Guided Protein Evolution Zhanghan Ni, Shengchao Liu, Hongyu Guo, Anima Anandkumar

NeurIPSW 2024 Language Models for Text-Guided Protein Evolution Zhanghan Ni, Shengchao Liu, Anima Anandkumar

ICMLW 2024 MINI-SEQUENCE TRANSFORMER: Optimizing Intermediate Memory for Long Sequences Training Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Anima Anandkumar

ICMLW 2024 Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design Shengchao Liu, Liang Yan, Weitao Du, Weiyang Liu, Hongyu Guo, Christian Borgs, Jennifer T Chayes, Anima Anandkumar

NeurIPS 2024 Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Anima Anandkumar

TMLR 2024 Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs Jean Kossaifi, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar

ICML 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

ICLRW 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

CVPR 2024 PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao, Bo Li, Anima Anandkumar

ICLRW 2024 Physics-Informed Neural Networks for Sampling Jingtong Sun, Julius Berner, Kamyar Azizzadenesheli, Anima Anandkumar

NeurIPS 2024 Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

TMLR 2024 Prismer: A Vision-Language Model with Multi-Task Experts Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, Anima Anandkumar

NeurIPSW 2024 Projected Low-Rank Gradient in Diffusion-Based Models for Inverse Problems Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar

ICLR 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli

NeurIPSW 2024 Scale-Consistent Learning with Neural Operators Zongyi Li, Samuel Lanthaler, Catherine Deng, Yixuan Wang, Kamyar Azizzadenesheli, Anima Anandkumar

ICML 2024 Solving Poisson Equations Using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, Anima Anandkumar

ICLRW 2024 Solving Poisson Equations Using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, Anima Anandkumar

NeurIPSW 2024 Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition Robert Joseph George, David Pitt, Jiawei Zhao, Jean Kossaifi, Cheng Luo, Yuandong Tian, Anima Anandkumar

ICMLW 2024 Towards Enforcing Hard Physics Constraints in Operator Learning Frameworks Valentin Duruisseaux, Miguel Liu-Schiaffini, Julius Berner, Anima Anandkumar

NeurIPSW 2024 Understanding Protein-DNA Interactions by Paying Attention to Protein and Genomics Foundation Models Dhruva Rajwade, Erica Wang, Aryan Satpathy, Alexander Brace, Hongyu Guo, Arvind Ramanathan, Shengchao Liu, Anima Anandkumar

NeurIPSW 2024 Unifying Subsampling Pattern Variations for Compressed Sensing MRI with Neural Operators Armeet Singh Jatyani, Jiayun Wang, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar

TMLR 2024 Voyager: An Open-Ended Embodied Agent with Large Language Models Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar

CVPRW 2024 What Is Point Supervision Worth in Video Instance Segmentation? Shuaiyi Huang, De-An Huang, Zhiding Yu, Shiyi Lan, Subhashree Radhakrishnan, José M. Álvarez, Abhinav Shrivastava, Anima Anandkumar

ICMLW 2023 AutoBiasTest: Controllable Test Sentence Generation for Open-Ended Social Bias Testing in Language Models at Scale Rafal Dariusz Kocielnik, Shrimai Prabhumoye, Vivian L Zhang, R. Michael Alvarez, Anima Anandkumar

ICLR 2023 DensePure: Understanding Diffusion Models for Adversarial Robustness Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

TMLR 2023 Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data Yuji Roh, Weili Nie, De-An Huang, Steven Euijong Whang, Arash Vahdat, Anima Anandkumar

NeurIPSW 2023 Empowering Domain Experts to Detect Social Bias in Generative AI with User-Friendly Interfaces Roy Jiang, Rafal Kocielnik, Adhithya Prakash Saravanan, Pengrui Han, R. Michael Alvarez, Anima Anandkumar

ICCV 2023 End-to-End 3D Tracking with Decoupled Queries Yanwei Li, Zhiding Yu, Jonah Philion, Anima Anandkumar, Sanja Fidler, Jiaya Jia, Jose Alvarez

NeurIPSW 2023 Eureka: Human-Level Reward Design via Coding Large Language Models Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar

NeurIPSW 2023 Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models Adhithya Prakash Saravanan, Rafal Kocielnik, Roy Jiang, Pengrui Han, Anima Anandkumar

ICCV 2023 FB-BEV: BEV Representation from Forward-Backward View Transformations Zhiqi Li, Zhiding Yu, Wenhai Wang, Anima Anandkumar, Tong Lu, Jose M. Alvarez

CVPR 2023 Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids Wei Dong, Christopher Choy, Charles Loop, Or Litany, Yuke Zhu, Anima Anandkumar

ICML 2023 Fast Sampling of Diffusion Models via Operator Learning Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar

ICCV 2023 FocalFormer3D: Focusing on Hard Instance for 3D Object Detection Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Anima Anandkumar, Jiaya Jia, Jose M. Alvarez

JMLR 2023 Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zongyi Li, Daniel Zhengyu Huang, Burigede Liu, Anima Anandkumar

ICCV 2023 Fully Attentional Networks with Self-Emerging Token Labeling Bingyin Zhao, Zhiding Yu, Shiyi Lan, Yutao Cheng, Anima Anandkumar, Yingjie Lao, Jose M. Alvarez

ICML 2023 I$^2$SB: Image-to-Image Schrödinger Bridge Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos Theodorou, Weili Nie, Anima Anandkumar

ICMLW 2023 Incremental Low-Rank Learning Jiawei Zhao, Yifei Zhang, Beidi Chen, Florian Tobias Schaefer, Anima Anandkumar

ICMLW 2023 Incrementally-Computable Neural Networks: Efficient Inference for Dynamic Inputs Or Sharir, Anima Anandkumar

CoRL 2023 MimicPlay: Long-Horizon Imitation Learning by Watching Human Play Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, Anima Anandkumar

JMLR 2023 Neural Operator: Learning Maps Between Function Spaces with Applications to PDEs Nikola Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar

NeurIPSW 2023 Physics-Informed Neural Operators with Exact Differentiation on Arbitrary Geometries Colin White, Julius Berner, Jean Kossaifi, Mogab Elleithy, David Pitt, Daniel Leibovici, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar

ICLR 2023 Retrieval-Based Controllable Molecule Generation Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard Baraniuk, Anima Anandkumar

ICCV 2023 Spacetime Surface Regularization for Neural Dynamic Scene Reconstruction Jaesung Choe, Christopher Choy, Jaesik Park, In So Kweon, Anima Anandkumar

ICML 2023 Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar

ICMLW 2023 Stochastic Linear Bandits with Unknown Safety Constraints and Local Feedback K Nithin Varma, Sahin Lale, Anima Anandkumar

NeurIPSW 2023 Towards Large Language Models as Copilots for Theorem Proving in Lean Peiyang Song, Kaiyu Yang, Anima Anandkumar

ICML 2023 VIMA: 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

CVPR 2023 Vision Transformers Are Good Mask Auto-Labelers Shiyi Lan, Xitong Yang, Zhiding Yu, Zuxuan Wu, Jose M. Alvarez, Anima Anandkumar

CVPR 2023 VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion Yiming Li, Zhiding Yu, Christopher Choy, Chaowei Xiao, Jose M. Alvarez, Sanja Fidler, Chen Feng, Anima Anandkumar

NeurIPSW 2023 Voyager: An Open-Ended Embodied Agent with Large Language Models Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar

ECCV 2022 AdvDO: Realistic Adversarial Attacks for Trajectory Prediction Yulong Cao, Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone

ECCV 2022 Augmenting Deep Classifiers with Polynomial Neural Networks Grigorios G. Chrysos, Markos Georgopoulos, Jiankang Deng, Jean Kossaifi, Yannis Panagakis, Anima Anandkumar

CVPR 2022 Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions Huaizu Jiang, Xiaojian Ma, Weili Nie, Zhiding Yu, Yuke Zhu, Anima Anandkumar

NeurIPSW 2022 DensePure: Understanding Diffusion Models Towards Adversarial Robustness Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

ICLR 2022 Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators John Guibas, Morteza Mardani, Zongyi Li, Andrew Tao, Anima Anandkumar, Bryan Catanzaro

NeurIPS 2022 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

NeurIPSW 2022 Fast Sampling of Diffusion Models via Operator Learning Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar

NeurIPS 2022 Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar

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

TMLR 2022 Generative Adversarial Neural Operators Md Ashiqur Rahman, Manuel A Florez, Anima Anandkumar, Zachary E Ross, Kamyar Azizzadenesheli

NeurIPS 2022 Learning Chaotic Dynamics in Dissipative Systems Zongyi Li, Miguel Liu-Schiaffini, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar

NeurIPS 2022 MinVIS: A Minimal Video Instance Segmentation Framework Without Video-Based Training De-An Huang, Zhiding Yu, Anima Anandkumar

NeurIPS 2022 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

CVPR 2022 Not All Labels Are Equal: Rationalizing the Labeling Costs for Training Object Detection Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, Jose M. Alvarez

CVPR 2022 Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers Zhiqi Li, Wenhai Wang, Enze Xie, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo, Tong Lu

NeurIPS 2022 PeRFception: Perception Using Radiance Fields Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Chris Choy, Anima Anandkumar, Minsu Cho, Jaesik Park

NeurIPS 2022 Pre-Trained 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

ICLR 2022 RelViT: Concept-Guided Vision Transformer for Visual Relational Reasoning Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar

CoRL 2022 Robust Trajectory Prediction Against Adversarial Attacks Yulong Cao, Danfei Xu, Xinshuo Weng, Zhuoqing Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone

NeurIPS 2022 Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao

NeurIPSW 2022 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

TMLR 2022 ZerO Initialization: Initializing Neural Networks with Only Zeros and Ones Jiawei Zhao, Florian Tobias Schaefer, Anima Anandkumar

CoRL 2021 Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization Youngwoon Lee, Joseph J Lim, Anima Anandkumar, Yuke Zhu

NeurIPS 2021 Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions Jiachen Sun, Yulong Cao, Christopher B Choy, Zhiding Yu, Anima Anandkumar, Zhuoqing Morley Mao, Chaowei Xiao

NeurIPS 2021 AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang

ICML 2021 Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar

UAI 2021 Competitive Policy Optimization Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar

ICLR 2021 Contrastive Syn-to-Real Generalization Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez, Zhangyang Wang, Anima Anandkumar

NeurIPS 2021 Controllable and Compositional Generation with Latent-Space Energy-Based Models Weili Nie, Arash Vahdat, Anima Anandkumar

NeurIPS 2021 Coupled Segmentation and Edge Learning via Dynamic Graph Propagation Zhiding Yu, Rui Huang, Wonmin Byeon, Sifei Liu, Guilin Liu, Thomas Breuel, Anima Anandkumar, Jan Kautz

ICCV 2021 DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Shiyi Lan, Zhiding Yu, Christopher Choy, Subhashree Radhakrishnan, Guilin Liu, Yuke Zhu, Larry S. Davis, Anima Anandkumar

L4DC 2021 Finite-Time System Identification and Adaptive Control in Autoregressive Exogenous Systems Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

ICLR 2021 Fourier Neural Operator for Parametric Partial Differential Equations Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar

NeurIPS 2021 Long-Short Transformer: Efficient Transformers for Language and Vision Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro

NeurIPS 2021 SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo

ICCV 2021 Self-Calibrating Neural Radiance Fields Yoonwoo Jeong, Seokjun Ahn, Christopher Choy, Anima Anandkumar, Minsu Cho, Jaesik Park

L4DC 2021 Stability and Identification of Random Asynchronous Linear Time-Invariant Systems Sahin Lale, Oguzhan Teke, Babak Hassibi, Anima Anandkumar

L4DC 2021 Stable Online Control of Linear Time-Varying Systems Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman

NeurIPS 2021 Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar

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

NeurIPS 2020 Causal Discovery in Physical Systems from Videos Yunzhu Li, Antonio Torralba, Anima Anandkumar, Dieter Fox, Animesh Garg

NeurIPS 2020 Convolutional Tensor-Train LSTM for Spatio-Temporal Learning Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar

NeurIPS 2020 Learning Compositional Functions via Multiplicative Weight Updates Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue

CoRL 2020 Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg

NeurIPS 2020 Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

NeurIPS 2020 Multipole Graph Neural Operator for Parametric Partial Differential Equations Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew Stuart, Kaushik Bhattacharya, Anima Anandkumar

NeurIPS 2020 Neural Networks with Recurrent Generative Feedback Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Tsao, Anima Anandkumar

ICLRW 2020 Neural Operator: Graph Kernel Network for Partial Differential Equations Anima Anandkumar, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Nikola Kovachki, Zongyi Li, Burigede Liu, Andrew Stuart

L4DC 2020 Robust Regression for Safe Exploration in Control Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue

JMLR 2020 Tensor Regression Networks Jean Kossaifi, Zachary C. Lipton, Arinbjorn Kolbeinsson, Aran Khanna, Tommaso Furlanello, Anima Anandkumar

ICLR 2019 Active Learning with Partial Feedback Peiyun Hu, Zachary C. Lipton, Anima Anandkumar, Deva Ramanan

ICMLW 2019 Angular Visual Hardness Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Anima Anandkumar

NeurIPSW 2019 Brain-Inspired Robust Vision Using Convolutional Neural Networks with Feedback Yujia Huang, Sihui Dai, Tan Nguyen, Pinglei Bao, Doris Y. Tsao, Richard G. Baraniuk, Anima Anandkumar

NeurIPS 2019 Competitive Gradient Descent Florian Schaefer, Anima Anandkumar

UAI 2019 Guaranteed Scalable Learning of Latent Tree Models Furong Huang, Niranjan Uma Naresh, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar

FnTML 2019 Spectral Learning on Matrices and Tensors Majid Janzamin, Rong Ge, Jean Kossaifi, Anima Anandkumar

MLOSS 2019 TensorLy: Tensor Learning in Python Jean Kossaifi, Yannis Panagakis, Anima Anandkumar, Maja Pantic

ICLR 2019 signSGD with Majority Vote Is Communication Efficient and Fault Tolerant Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar

ICML 2018 Born Again Neural Networks Tommaso Furlanello, Zachary Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar

COLT 2017 Homotopy Analysis for Tensor PCA Anima Anandkumar, Yuan Deng, Rong Ge, Hossein Mobahi

AISTATS 2017 Spectral Methods for Correlated Topic Models Forough Arabshahi, Anima Anandkumar

CVPRW 2017 Tensor Contraction Layers for Parsimonious Deep Nets Jean Kossaifi, Aran Khanna, Zachary C. Lipton, Tommaso Furlanello, Anima Anandkumar

NeurIPS 2016 Online and Differentially-Private Tensor Decomposition Yining Wang, Anima Anandkumar

AISTATS 2016 Provable Tensor Methods for Learning Mixtures of Generalized Linear Models Hanie Sedghi, Majid Janzamin, Anima Anandkumar

AISTATS 2016 Tensor vs. Matrix Methods: Robust Tensor Decomposition Under Block Sparse Perturbations Anima Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan

NeurIPS 2015 Fast and Guaranteed Tensor Decomposition via Sketching Yining Wang, Hsiao-Yu Tung, Alexander J Smola, Anima Anandkumar

ICLR 2015 Provable Methods for Training Neural Networks with Sparse Connectivity Hanie Sedghi, Anima Anandkumar

ICLR 2015 Score Function Features for Discriminative Learning Majid Janzamin, Hanie Sedghi, Anima Anandkumar

ALT 2015 Tensor Decompositions for Learning Latent Variable Models (a Survey for ALT) Anima Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade, Matus Telgarsky

NeurIPS 2014 Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition Hanie Sedghi, Anima Anandkumar, Edmond Jonckheere

NeurIPS 2013 When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity Anima Anandkumar, Daniel J. Hsu, Majid Janzamin, Sham M. Kakade

NeurIPS 2012 A Spectral Algorithm for Latent Dirichlet Allocation Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-kai Liu

NeurIPS 2012 Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs Anima Anandkumar, Ragupathyraj Valluvan

NeurIPS 2012 Learning Mixtures of Tree Graphical Models Anima Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade