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ORCIDAnima Anandkumar
Animashree Anandkumar
Person information
- affiliation: California Institute of Technology, Pasadena, USA
- affiliation: NVIDIA, USA
- affiliation (former): University of California Irvine, Center for Pervasive Communications and Computing
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2020 – today
- 2024
[j58]Rafal Kocielnik, Zhuofang Li, Claudia Kann, Deshawn Sambrano, Jacob Morrier, Mitchell Linegar, Carly Taylor, Min Kim, Nabiha Naqvie, Feri Soltani, Arman Dehpanah, Grant Cahill, Animashree Anandkumar, R. Michael Alvarez:
Challenges in moderating disruptive player behavior in online competitive action games. Frontiers Comput. Sci. 6 (2024)- [j57]Bokui Shen
, Zhenyu Jiang, Christopher Bongsoo Choy, Silvio Savarese, Leonidas J. Guibas, Anima Anandkumar, Yuke Zhu:
Action-conditional implicit visual dynamics for deformable object manipulation. Int. J. Robotics Res. 43(4): 437-455 (2024) - [j56]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
State-specific protein-ligand complex structure prediction with a multiscale deep generative model. Nat. Mac. Intell. 6(2): 195-208 (2024) - [j55]Rafal Kocielnik, Cherine H. Yang, Runzhuo Ma, Steven Y. Cen, Elyssa Y. Wong, Timothy N. Chu, J. Everett Knudsen, Peter Wager, John Heard, Umar Ghaffar, Anima Anandkumar, Andrew J. Hung:
Human AI collaboration for unsupervised categorization of live surgical feedback. npj Digit. Medicine 7(1) (2024) - [j54]Jie Feng, Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman:
Stability Constrained Reinforcement Learning for Decentralized Real-Time Voltage Control. IEEE Trans. Control. Netw. Syst. 11(3): 1370-1381 (2024) - [j53]Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, Anima Anandkumar:
Prismer: A Vision-Language Model with Multi-Task Experts. Trans. Mach. Learn. Res. 2024 (2024) - [j52]Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar:
Voyager: An Open-Ended Embodied Agent with Large Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [j51]Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar:
Fast Training of Diffusion Models with Masked Transformers. Trans. Mach. Learn. Res. 2024 (2024) - [c206]Shuaiyi Huang, De-An Huang, Zhiding Yu, Shiyi Lan, Subhashree Radhakrishnan, José M. Álvarez, Abhinav Shrivastava, Anima Anandkumar:
What is Point Supervision Worth in Video Instance Segmentation? CVPR Workshops 2024: 2671-2681 - [c205]Zetong Yang, Zhiding Yu, Christopher B. Choy, Renhao Wang, Anima Anandkumar, José M. Álvarez:
Improving Distant 3D Object Detection Using 2D Box Supervision. CVPR 2024: 14853-14863 - [c204]Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao, Bo Li, Anima Anandkumar:
Perada: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees. CVPR 2024: 23838-23848 - [c203]Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli:
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. ICLR 2024 - [c202]Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar:
Eureka: Human-Level Reward Design via Coding Large Language Models. ICLR 2024 - [c201]Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar:
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. ICLR 2024 - [c200]Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar:
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. ICLR 2024 - [c199]Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu:
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. ICML 2024 - [c198]Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar:
Neural Operators with Localized Integral and Differential Kernels. ICML 2024 - [c197]Logan Murphy, Kaiyu Yang, Jialiang Sun, Zhaoyu Li, Anima Anandkumar, Xujie Si:
Autoformalizing Euclidean Geometry. ICML 2024 - [c196]Hong Chul Nam, Julius Berner, Anima Anandkumar:
Solving Poisson Equations using Neural Walk-on-Spheres. ICML 2024 - [c195]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML 2024 - [c194]Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. ICML 2024 - [c193]Shuaiyi Huang, Mara Levy, Zhenyu Jiang, Anima Anandkumar, Yuke Zhu, Linxi Fan, De-An Huang, Abhinav Shrivastava:
ARDuP: Active Region Video Diffusion for Universal Policies. IROS 2024: 8465-8472 - [c192]Renhao Wang, Zhiding Yu, Shiyi Lan, Enze Xie, Ke Chen, Anima Anandkumar, José M. Álvarez:
SF3D: SlowFast Temporal 3D Object Detection. IV 2024: 1280-1285 - [c191]Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. SC 2024: 7 - [c190]Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar:
Differentially Private Video Activity Recognition. WACV 2024: 6643-6653 - [i276]Bingyin Zhao, Zhiding Yu, Shiyi Lan, Yutao Cheng, Anima Anandkumar, Yingjie Lao, José M. Álvarez:
Fully Attentional Networks with Self-emerging Token Labeling. CoRR abs/2401.03844 (2024) - [i275]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR abs/2401.11037 (2024) - [i274]Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh C. Bhethanabotla, Nakul Rampal, Omar Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T. Chayes:
A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics. CoRR abs/2401.15122 (2024) - [i273]Ziqi Ma, Kamyar Azizzadenesheli, Anima Anandkumar:
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction. CoRR abs/2402.01960 (2024) - [i272]Pengrui Han, Rafal Kocielnik, Adhithya Prakash Saravanan, Roy Jiang, Or Sharir, Anima Anandkumar:
ChatGPT Based Data Augmentation for Improved Parameter-Efficient Debiasing of LLMs. CoRR abs/2402.11764 (2024) - [i271]Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar:
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching. CoRR abs/2402.14167 (2024) - [i270]Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar:
Neural Operators with Localized Integral and Differential Kernels. CoRR abs/2402.16845 (2024) - [i269]Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. CoRR abs/2403.03507 (2024) - [i268]Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu:
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. CoRR abs/2403.03542 (2024) - [i267]Zetong Yang, Zhiding Yu, Christopher B. Choy, Renhao Wang, Anima Anandkumar, José M. Álvarez:
Improving Distant 3D Object Detection Using 2D Box Supervision. CoRR abs/2403.09230 (2024) - [i266]Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel V. Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar:
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. CoRR abs/2403.12553 (2024) - [i265]Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar:
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. CoRR abs/2403.14148 (2024) - [i264]Shuaiyi Huang, De-An Huang, Zhiding Yu, Shiyi Lan, Subhashree Radhakrishnan, José M. Álvarez, Abhinav Shrivastava, Anima Anandkumar:
What is Point Supervision Worth in Video Instance Segmentation? CoRR abs/2404.01990 (2024) - [i263]Peiyang Song, Kaiyu Yang, Anima Anandkumar:
Towards Large Language Models as Copilots for Theorem Proving in Lean. CoRR abs/2404.12534 (2024) - [i262]Logan Murphy, Kaiyu Yang, Jialiang Sun, Zhaoyu Li, Anima Anandkumar, Xujie Si:
Autoformalizing Euclidean Geometry. CoRR abs/2405.17216 (2024) - [i261]Hong Chul Nam, Julius Berner, Anima Anandkumar:
Solving Poisson Equations using Neural Walk-on-Spheres. CoRR abs/2406.03494 (2024) - [i260]Shuaiyi Huang, Mara Levy, Zhenyu Jiang, Anima Anandkumar, Yuke Zhu, Linxi Fan, De-An Huang, Abhinav Shrivastava:
ARDuP: Active Region Video Diffusion for Universal Policies. CoRR abs/2406.13301 (2024) - [i259]Bingliang Zhang, Wenda Chu, Julius Berner, Chenlin Meng, Anima Anandkumar, Yang Song:
Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing. CoRR abs/2407.01521 (2024) - [i258]Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Müller, Kamyar Azizzadenesheli, Anima Anandkumar:
Dynamical Measure Transport and Neural PDE Solvers for Sampling. CoRR abs/2407.07873 (2024) - [i257]Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Anima Anandkumar:
MINI-SEQUENCE TRANSFORMER: Optimizing Intermediate Memory for Long Sequences Training. CoRR abs/2407.15892 (2024) - [i256]Chuwei Wang, Julius Berner, Zongyi Li, Di Zhou, Jiayun Wang, Jane Bae, Anima Anandkumar:
Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators. CoRR abs/2408.05177 (2024) - [i255]Freya Shah, Taylor L. Patti, Julius Berner, Bahareh Tolooshams, Jean Kossaifi, Anima Anandkumar:
Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems. CoRR abs/2409.03302 (2024) - [i254]Shengchao Liu, Divin Yan, Weitao Du, Weiyang Liu, Zhuoxinran Li, Hongyu Guo, Christian Borgs, Jennifer T. Chayes, Anima Anandkumar:
Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design. CoRR abs/2409.10584 (2024) - [i253]Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Anima Anandkumar, Furong Huang:
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. CoRR abs/2409.18433 (2024) - [i252]Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar:
Diffusion State-Guided Projected Gradient for Inverse Problems. CoRR abs/2410.03463 (2024) - [i251]Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar:
LeanAgent: Lifelong Learning for Formal Theorem Proving. CoRR abs/2410.06209 (2024) - [i250]Armeet Singh Jatyani, Jiayun Wang, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar:
Unifying Subsampling Pattern Variations for Compressed Sensing MRI with Neural Operators. CoRR abs/2410.16290 (2024) - [i249]Zhuofang Li, Rafal Kocielnik, Mitchell Linegar, Deshawn Sambrano, Fereshteh Soltani, Min Kim, Nabiha Naqvie, Grant Cahill, Animashree Anandkumar, R. Michael Alvarez:
Online Moderation in Competitive Action Games: How Intervention Affects Player Behaviors. CoRR abs/2411.01057 (2024) - [i248]Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa:
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. CoRR abs/2411.10548 (2024) - [i247]Arushi Gupta, Rafal Kocielnik, Jiayun Wang, Firdavs Nasriddinov, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung:
Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessment. CoRR abs/2411.10919 (2024) - 2023
- [j50]Andrew J. Hung, Richard Bao, Idris O. Sunmola, De-An Huang, Jessica H. Nguyen, Anima Anandkumar:
Capturing fine-grained details for video-based automation of suturing skills assessment. Int. J. Comput. Assist. Radiol. Surg. 18(3): 545-552 (2023) - [j49]Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia A. Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro:
#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. 37(1): 28-44 (2023) - [j48]Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j47]Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs. J. Mach. Learn. Res. 24: 89:1-89:97 (2023) - [j46]Zongyi Li, Daniel Zhengyu Huang, Burigede Liu, Anima Anandkumar:
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries. J. Mach. Learn. Res. 24: 388:1-388:26 (2023) - [j45]Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar:
Multi-modal molecule structure-text model for text-based retrieval and editing. Nat. Mac. Intell. 5(12): 1447-1457 (2023) - [j44]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j43]Dani Kiyasseh, Jasper Laca, Taseen F. Haque, Maxwell X. Otiato, Brian J. Miles, Christian Wagner, Daniel A. Donoho, Quoc-Dien Trinh, Animashree Anandkumar, Andrew J. Hung:
Human visual explanations mitigate bias in AI-based assessment of surgeon skills. npj Digit. Medicine 6 (2023) - [j42]Taylor L. Patti, Jean Kossaifi, Anima Anandkumar, Susanne F. Yelin:
Quantum Goemans-Williamson Algorithm with the Hadamard Test and Approximate Amplitude Constraints. Quantum 7: 1057 (2023) - [j41]Yuji Roh, Weili Nie, De-An Huang, Steven Euijong Whang, Arash Vahdat, Anima Anandkumar:
Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data. Trans. Mach. Learn. Res. 2023 (2023) - [c189]Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar:
Distributionally Robust Policy Gradient for Offline Contextual Bandits. AISTATS 2023: 6443-6462 - [c188]Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi:
Thompson Sampling for Partially Observable Linear-Quadratic Control. ACC 2023: 4561-4568 - [c187]Benyamin Allahgholizadeh Haghi, Lin Ma, Sahin Lale, Anima Anandkumar, Azita Emami:
EKGNet: A 10.96μW Fully Analog Neural Network for Intra-Patient Arrhythmia Classification. BioCAS 2023: 1-5 - [c186]Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar:
KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems. CDC 2023: 1334-1341 - [c185]Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, Anima Anandkumar:
MimicPlay: Long-Horizon Imitation Learning by Watching Human Play. CoRL 2023: 201-221 - [c184]Wei Dong, Christopher B. Choy, Charles Loop, Or Litany, Yuke Zhu, Anima Anandkumar:
Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids. CVPR 2023: 4263-4272 - [c183]Yiming Li, Zhiding Yu, Christopher B. Choy, Chaowei Xiao, José M. Álvarez, Sanja Fidler, Chen Feng, Anima Anandkumar:
VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion. CVPR 2023: 9087-9098 - [c182]Shiyi Lan, Xitong Yang, Zhiding Yu, Zuxuan Wu, José M. Álvarez, Anima Anandkumar:
Vision Transformers are Good Mask Auto-Labelers. CVPR 2023: 23745-23755 - [c181]Dan Su, Mostofa Patwary, Shrimai Prabhumoye, Peng Xu, Ryan Prenger, Mohammad Shoeybi, Pascale Fung, Anima Anandkumar, Bryan Catanzaro:
Context Generation Improves Open Domain Question Answering. EACL (Findings) 2023: 781-796 - [c180]Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro:
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study. EMNLP 2023: 7763-7786 - [c179]Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Mohammad Shoeybi, Ming-Yu Liu, Yuke Zhu, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar:
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. EMNLP (Findings) 2023: 11844-11857 - [c178]Adhithya Prakash Saravanan, Rafal Kocielnik, Roy Jiang, Pengrui Han, Anima Anandkumar:
Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models. ICBINB 2023: 84-102 - [c177]Bingyin Zhao, Zhiding Yu, Shiyi Lan, Yutao Cheng, Anima Anandkumar, Yingjie Lao, José M. Álvarez:
Fully Attentional Networks with Self-emerging Token Labeling. ICCV 2023: 5562-5572 - [c176]Zhiqi Li, Zhiding Yu, Wenhai Wang, Anima Anandkumar, Tong Lu, José M. Álvarez:
FB-BEV: BEV Representation from Forward-Backward View Transformations. ICCV 2023: 6896-6905 - [c175]Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Anima Anandkumar, Jiaya Jia, José M. Álvarez:
FocalFormer3D : Focusing on Hard Instance for 3D Object Detection. ICCV 2023: 8360-8371 - [c174]Jaesung Choe, Christopher B. Choy, Jaesik Park, In So Kweon, Anima Anandkumar:
Spacetime Surface Regularization for Neural Dynamic Scene Reconstruction. ICCV 2023: 17825-17835 - [c173]Yanwei Li, Zhiding Yu, Jonah Philion, Anima Anandkumar, Sanja Fidler, Jiaya Jia, Jose Alvarez:
End-to-end 3D Tracking with Decoupled Queries. ICCV 2023: 18256-18265 - [c172]Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar:
Retrieval-based Controllable Molecule Generation. ICLR 2023 - [c171]Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song:
DensePure: Understanding Diffusion Models for Adversarial Robustness. ICLR 2023 - [c170]Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar:
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. ICML 2023: 2806-2823 - [c169]Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, Linxi Fan:
VIMA: Robot Manipulation with Multimodal Prompts. ICML 2023: 14975-15022 - [c168]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
I2SB: Image-to-Image Schrödinger Bridge. ICML 2023: 22042-22062 - [c167]Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar:
Fast Sampling of Diffusion Models via Operator Learning. ICML 2023: 42390-42402 - [c166]Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan:
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. IJCAI 2023: 1460-1469 - [c165]Anima Anandkumar:
Neural Operators for Solving PDEs and Inverse Design. ISPD 2023: 195 - [c164]Rafal Kocielnik, Elyssa Y. Wong, Timothy N. Chu, Lydia Lin, De-An Huang, Jiayun Wang, Anima Anandkumar, Andrew J. Hung:
Deep Multimodal Fusion for Surgical Feedback Classification. ML4H@NeurIPS 2023: 256-267 - [c163]Zongyi Li, Nikola B. Kovachki, Christopher B. Choy, Boyi Li, Jean Kossaifi, Shourya Prakash Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Animashree Anandkumar:
Geometry-Informed Neural Operator for Large-Scale 3D PDEs. NeurIPS 2023 - [c162]Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang:
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. NeurIPS 2023 - [c161]Kaiyu Yang, Aidan M. Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan J. Prenger, Animashree Anandkumar:
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. NeurIPS 2023 - [c160]Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard:
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS 2023 - [c159]Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar:
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. PASC 2023: 13:1-13:11 - [d2]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
NeuralPLexer evaluation datasets and predictions. Zenodo, 2023
- [i246]Shiyi Lan, Xitong Yang, Zhiding Yu, Zuxuan Wu, José M. Álvarez, Anima Anandkumar:
Vision Transformers Are Good Mask Auto-Labelers. CoRR abs/2301.03992 (2023) - [i245]Peter I Renn, Cong Wang, Sahin Lale, Zongyi Li, Anima Anandkumar, Morteza Gharib:
Forecasting subcritical cylinder wakes with Fourier Neural Operators. CoRR abs/2301.08290 (2023) - [i244]Shengchao Liu, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Anthony Gitter, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar:
A Text-guided Protein Design Framework. CoRR abs/2302.04611 (2023) - [i243]Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Ming-Yu Liu, Yuke Zhu, Mohammad Shoeybi, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar:
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. CoRR abs/2302.04858 (2023) - [i242]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
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