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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
- 2026
[i314]Thomas Y. L. Lin, Jiachen Yao, Lufang Chiang, Julius Berner, Anima Anandkumar:
Decoupled Diffusion Sampling for Inverse Problems on Function Spaces. CoRR abs/2601.23280 (2026)- 2025
- [j69]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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. 18(4): 385-912 (2025) - [j68]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:
Score-Based Diffusion Models in Function Space. J. Mach. Learn. Res. 26: 158:1-158:62 (2025) - [j67]Xinyi Li, Zongyi Li, Nikola B. Kovachki, Anima Anandkumar:
Geometric Operator Learning with Optimal Transport. J. Mach. Learn. Res. 26: 282:1-282:38 (2025) - [j66]Shengchao Liu, Yanjing Li, Zhuoxinran Li, Anthony Gitter, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Arvind Ramanathan, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar:
A text-guided protein design framework. Nat. Mac. Intell. 7(4): 580-591 (2025) - [j65]Rafal Kocielnik, Zhuofang Li, 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. Proc. ACM Hum. Comput. Interact. 9(6): 96-130 (2025) - [j64]Abhishek Chakraborty, Taylor L. Patti, Brucek Khailany, Andrew N. Jordan, Anima Anandkumar:
GPU-accelerated Effective Hamiltonian Calculator. Quantum 9: 1946 (2025) - [j63]Robert Joseph George, Suozhi Huang, Peiyang Song, Anima Anandkumar:
LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction. Trans. Mach. Learn. Res. 2025 (2025) - [j62]Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel V. Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar:
Enabling Automatic Differentiation with Mollified Graph Neural Operators. Trans. Mach. Learn. Res. 2025 (2025) - [c222]Bingliang Zhang, Wenda Chu, Julius Berner, Chenlin Meng, Anima Anandkumar, Yang Song:
Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing. CVPR 2025: 20895-20905 - [c221]Armeet Singh Jatyani, Jiayun Wang, Aditi Chandrashekar, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar:
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns. CVPR 2025: 26004-26013 - [c220]Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar:
Sequential Controlled Langevin Diffusions. ICLR 2025 - [c219]Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar:
LeanAgent: Lifelong Learning for Formal Theorem Proving. ICLR 2025 - [c218]Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar:
Robust Representation Consistency Model via Contrastive Denoising. ICLR 2025 - [c217]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. ICLR 2025 - [c216]Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar:
Diffusion State-Guided Projected Gradient for Inverse Problems. ICLR 2025 - [c215]Peiyang Song, Kaiyu Yang, Anima Anandkumar:
Lean Copilot: Large Language Models as Copilots for Theorem Proving in Lean. NeuS 2025: 144-169 - [c214]Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Setty, Aswathy Ajith, J. Gregory Pauloski, Varuni Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan:
HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. PASC 2025: 1-13 - [c213]Myrl G. Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar:
Off-policy Predictive Control with Causal Sensitivity Analysis. UAI 2025: 2958-2972 - [d4]Julius Berner, Miguel Liu-Schiaffini, Jean Kossaifi, Valentin Duruisseaux, Boris Bonev, Kamyar Azizzadenesheli, Anima Anandkumar:
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning (Dataset). Zenodo, 2025
- [i313]Jiayun Wang, Oleksii Ostras, Masashi Sode, Bahareh Tolooshams, Zongyi Li, Kamyar Azizzadenesheli, Gianmarco Pinton, Anima Anandkumar:
Ultrasound Lung Aeration Map via Physics-Aware Neural Operators. CoRR abs/2501.01157 (2025) - [i312]Robert Joseph George, David Pitt, Jiawei Zhao, Jean Kossaifi, Cheng Luo, Yuandong Tian, Anima Anandkumar:
Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition. CoRR abs/2501.02379 (2025) - [i311]Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Zhongjia Ba, Kui Ren, Jun Zhu, Anima Anandkumar:
Robust Representation Consistency Model via Contrastive Denoising. CoRR abs/2501.13094 (2025) - [i310]Cheng Luo, Zefan Cai, Hanshi Sun, Jinqi Xiao, Bo Yuan, Wen Xiao, Junjie Hu, Jiawei Zhao, Beidi Chen, Anima Anandkumar:
HeadInfer: Memory-Efficient LLM Inference by Head-wise Offloading. CoRR abs/2502.12574 (2025) - [i309]Suozhi Huang, Peiyang Song, Robert Joseph George, Anima Anandkumar:
LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction. CoRR abs/2502.17925 (2025) - [i308]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:
Fourier Neural Operator based surrogates for CO2 storage in realistic geologies. CoRR abs/2503.11031 (2025) - [i307]Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel V. Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar:
Enabling Automatic Differentiation with Mollified Graph Neural Operators. CoRR abs/2504.08277 (2025) - [i306]Junyang Zhang, Tianyi Zhu, Cheng Luo, Anima Anandkumar:
MOM: Memory-Efficient Offloaded Mini-Sequence Inference for Long Context Language Models. CoRR abs/2504.12526 (2025) - [i305]Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Vasanthakumari, Aswathy Ajith, J. Gregory Pauloski, Varuni Katti Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan:
HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. CoRR abs/2505.04846 (2025) - [i304]Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar:
Guided Diffusion Sampling on Function Spaces with Applications to PDEs. CoRR abs/2505.17004 (2025) - [i303]Bahareh Tolooshams, Aditi Chandrashekar, Rayhan Zirvi, Abbas Mammadov, Jiachen Yao, Chuwei Wang, Anima Anandkumar:
EquiReg: Equivariance Regularized Diffusion for Inverse Problems. CoRR abs/2505.22973 (2025) - [i302]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:
R-KV: Redundancy-aware KV Cache Compression for Training-Free Reasoning Models Acceleration. CoRR abs/2505.24133 (2025) - [i301]Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams, Philip H. Wong, Costas A. Anastassiou, Anima Anandkumar:
NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models. CoRR abs/2506.04536 (2025) - [i300]Zhuofang Li, Rafal Kocielnik, Fereshteh Soltani, Penphob Boonyarungsrit, Animashree Anandkumar, R. Michael Alvarez:
Self-Anchored Attention Model for Sample-Efficient Classification of Prosocial Text Chat. CoRR abs/2506.09259 (2025) - [i299]Julius Berner, Miguel Liu-Schiaffini, Jean Kossaifi, Valentin Duruisseaux, Boris Bonev, Kamyar Azizzadenesheli, Anima Anandkumar:
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning. CoRR abs/2506.10973 (2025) - [i298]Yixuan Wang, Ziming Liu, Zongyi Li, Anima Anandkumar, Thomas Y. Hou:
High precision PINNs in unbounded domains: application to singularity formulation in PDEs. CoRR abs/2506.19243 (2025) - [i297]Beomseok Kang, Vignesh C. Bhethanabotla, Amin Tavakoli, Maurice D. Hanisch, William A. Goddard III, Anima Anandkumar:
OrbitAll: A Unified Quantum Mechanical Representation Deep Learning Framework for All Molecular Systems. CoRR abs/2507.03853 (2025) - [i296]Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Michael S. Pritchard, Alexander Keller:
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale. CoRR abs/2507.12144 (2025) - [i295]Zongyi Li, Samuel Lanthaler, Catherine Deng, Michael Chen, Yixuan Wang, Kamyar Azizzadenesheli, Anima Anandkumar:
Scale-Consistent Learning for Partial Differential Equations. CoRR abs/2507.18813 (2025) - [i294]Xinyi Li, Zongyi Li, Nikola B. Kovachki, Anima Anandkumar:
Geometric Operator Learning with Optimal Transport. CoRR abs/2507.20065 (2025) - [i293]Rafal Kocielnik, Min Kim, Penphob Boonyarungsrit, Fereshteh Soltani, Deshawn Sambrano, Animashree Anandkumar, R. Michael Alvarez:
Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scale. CoRR abs/2508.05938 (2025) - [i292]Pengrui Han, Rafal Kocielnik, Peiyang Song, Ramit Debnath, Dean Mobbs, Anima Anandkumar, R. Michael Alvarez:
The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs. CoRR abs/2509.03730 (2025) - [i291]Bahareh Tolooshams, Ailsa Shen, Anima Anandkumar:
Sparse Autoencoder Neural Operators: Model Recovery in Function Spaces. CoRR abs/2509.03738 (2025) - [i290]Jiayun Wang, Yousuf Aborahama, Arya Khokhar, Yang Zhang, Chuwei Wang, Karteekeya Sastry, Julius Berner, Yilin Luo, Boris Bonev, Zongyi Li, Kamyar Azizzadenesheli, Lihong V. Wang, Anima Anandkumar:
Accelerating 3D Photoacoustic Computed Tomography with End-to-End Physics-Aware Neural Operators. CoRR abs/2509.09894 (2025) - [i289]Zelin Zhao, Zongyi Li, Kimia Hassibi, Kamyar Azizzadenesheli, Junchi Yan, Hyunji Jane Bae, Di Zhou, Anima Anandkumar:
Physics-informed Neural-operator Predictive Control for Drag Reduction in Turbulent Flows. CoRR abs/2510.03360 (2025) - [i288]Sara Kangaslahti, Danny Ebanks, Jean Kossaifi, Anqi Liu, R. Michael Alvarez, Animashree Anandkumar:
Analyzing Political Text at Scale with Online Tensor LDA. CoRR abs/2511.07809 (2025) - [i287]Jinqi Xiao, Cheng Luo, Lingyi Huang, Cheng Yang, Yang Sui, Huy Phan, Xiao Zang, Yibiao Ying, Zhexiang Tang, Anima Anandkumar, Bo Yuan:
EcoSpa: Efficient Transformer Training with Coupled Sparsity. CoRR abs/2511.11641 (2025) - [i286]Firdavs Nasriddinov, Rafal Kocielnik, Anima Anandkumar, Andrew J. Hung:
Generating Natural-Language Surgical Feedback: From Structured Representation to Domain-Grounded Evaluation. CoRR abs/2511.15159 (2025) - [i285]Robert Joseph George, Carson Eisenach, Udaya Ghai, Dominique Perrault-Joncas, Anima Anandkumar, Dean P. Foster:
BRIDGE: Building Representations In Domain Guided Program Verification. CoRR abs/2511.21104 (2025) - [i284]Valentin Duruisseaux, Jean Kossaifi, Anima Anandkumar:
Fourier Neural Operators Explained: A Practical Perspective. CoRR abs/2512.01421 (2025) - [i283]Nihaal Bhojwani, Chuwei Wang, Hai-Yang Wang, Chang Sun, Elias R. Most, Anima Anandkumar:
From Black Hole to Galaxy: Neural Operator: Framework for Accretion and Feedback Dynamics. CoRR abs/2512.01576 (2025) - [i282]Amin Tavakoli, Raswanth Murugan, Ozan Gökdemir, Arvind Ramanathan, Frances H. Arnold, Anima Anandkumar:
Self Distillation Fine-Tuning of Protein Language Models Improves Versatility in Protein Design. CoRR abs/2512.09329 (2025) - [i281]Aujasvit Datta, Jiayun Wang, Asad Aali, Armeet Singh Jatyani, Anima Anandkumar:
Resolution-Independent Neural Operators for Multi-Rate Sparse-View CT. CoRR abs/2512.12236 (2025) - 2024
- [j61]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) - [j60]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) - [j59]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) - [j58]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) - [j57]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) - [j56]Robert Joseph George, Jiawei Zhao, Jean Kossaifi, Zongyi Li, Anima Anandkumar:
Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs. Trans. Mach. Learn. Res. 2024 (2024) - [j55]Jean Kossaifi, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar:
Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs. Trans. Mach. Learn. Res. 2024 (2024) - [j54]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) - [j53]Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar:
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction. 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) - [c212]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 - [c211]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 - [c210]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 - [c209]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 - [c208]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 - [c207]Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar:
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. ICLR 2024 - [c206]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 - [c205]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: 17616-17635 - [c204]Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar:
Neural Operators with Localized Integral and Differential Kernels. ICML 2024: 32576-32594 - [c203]Logan Murphy, Kaiyu Yang, Jialiang Sun, Zhaoyu Li, Anima Anandkumar, Xujie Si:
Autoformalizing Euclidean Geometry. ICML 2024: 36847-36893 - [c202]Hong Chul Nam, Julius Berner, Anima Anandkumar:
Solving Poisson Equations using Neural Walk-on-Spheres. ICML 2024: 37277-37292 - [c201]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: 55015-55032 - [c200]Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. ICML 2024: 61121-61143 - [c199]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 - [c198]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 - [c197]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. ML4H@NeurIPS 2024: 440-455 - [c196]Firdavs Nasriddinov, Rafal Kocielnik, Arushi Gupta, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung:
Automating Feedback Analysis in Surgical Training: Detection, Categorization, and Assessment. ML4H@NeurIPS 2024: 787-804 - [c195]Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Animashree Anandkumar, Furong Huang:
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. NeurIPS 2024 - [c194]Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Animashree Anandkumar:
Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training. NeurIPS 2024 - [c193]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, Animashree Anandkumar:
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. NeurIPS 2024 - [c192]Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Animashree Anandkumar, Frances H. Arnold, Yisong Yue:
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. NeurIPS 2024 - [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 - [i280]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) - [i279]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) - [i278]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) - [i277]Ziqi Ma, Kamyar Azizzadenesheli, Anima Anandkumar:
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction. CoRR abs/2402.01960 (2024) - [i276]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) - [i275]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) - [i274]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) - [i273]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) - [i272]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) - [i271]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) - [i270]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) - [i269]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) - [i268]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) - [i267]Peiyang Song, Kaiyu Yang, Anima Anandkumar:
Towards Large Language Models as Copilots for Theorem Proving in Lean. CoRR abs/2404.12534 (2024) - [i266]Logan Murphy, Kaiyu Yang, Jialiang Sun, Zhaoyu Li, Anima Anandkumar, Xujie Si:
Autoformalizing Euclidean Geometry. CoRR abs/2405.17216 (2024) - [i265]Hong Chul Nam, Julius Berner, Anima Anandkumar:
Solving Poisson Equations using Neural Walk-on-Spheres. CoRR abs/2406.03494 (2024) - [i264]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) - [i263]Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Anima Anandkumar, Frances H. Arnold, Yisong Yue:
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. CoRR abs/2406.15669 (2024) - [i262]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) - [i261]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) - [i260]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) - [i259]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) - [i258]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) - [i257]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) - [i256]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) - [i255]Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar:
Diffusion State-Guided Projected Gradient for Inverse Problems. CoRR abs/2410.03463 (2024) - [i254]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) - [i253]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) - [i252]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) - [i251]Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. 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) - [i250]Arushi Gupta, Rafal Kocielnik, Jiayun Wang, Firdavs Nasriddinov,