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ORCIDAnima Anandkumar
Animashree Anandkumar
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- affiliation: University of California Irvine, Center for Pervasive Communications and Computing
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2020 – today
- 2022
[j34]Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural-Fly enables rapid learning for agile flight in strong winds. Sci. Robotics 7(66) (2022)- [i174]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:
Pre-Trained Language Models for Interactive Decision-Making. CoRR abs/2202.01771 (2022) - [i173]Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro:
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models. CoRR abs/2202.04173 (2022) - [i172]Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, Pedram Hassanzadeh, Karthik Kashinath, Animashree Anandkumar:
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR abs/2202.11214 (2022) - [i171]Xinlong Wang, Zhiding Yu, Shalini De Mello, Jan Kautz, Anima Anandkumar, Chunhua Shen, Jose M. Alvarez:
FreeSOLO: Learning to Segment Objects without Annotations. CoRR abs/2202.12181 (2022) - [i170]Bokui Shen, Zhenyu Jiang, Christopher B. Choy, Leonidas J. Guibas, Silvio Savarese, Anima Anandkumar, Yuke Zhu:
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation. CoRR abs/2203.06856 (2022) - [i169]Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Mark Kilgard, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing Ren:
Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks. CoRR abs/2203.08616 (2022) - [i168]Enze Xie, Zhiding Yu, Daquan Zhou, Jonah Philion, Anima Anandkumar, Sanja Fidler, Ping Luo, Jose M. Alvarez:
M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation. CoRR abs/2204.05088 (2022) - [i167]Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar:
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning. CoRR abs/2204.11167 (2022) - [i166]Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Anima Anandkumar, Jiashi Feng, Jose M. Alvarez:
Understanding The Robustness in Vision Transformers. CoRR abs/2204.12451 (2022) - [i165]Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar, Zachary E. Ross, Kamyar Azizzadenesheli:
Generative Adversarial Neural Operators. CoRR abs/2205.03017 (2022) - [i164]Dani Kiyasseh, Runzhuo Ma, Taseen F. Haque, Jessica H. Nguyen, Christian Wagner, Animashree Anandkumar, Andrew J. Hung:
Quantification of Robotic Surgeries with Vision-Based Deep Learning. CoRR abs/2205.03028 (2022) - 2021
- [j33]Arinbjörn Kolbeinsson
, Jean Kossaifi, Yannis Panagakis, Adrian Bulat, Animashree Anandkumar, Ioanna Tzoulaki, Paul M. Matthews:
Tensor Dropout for Robust Learning. IEEE J. Sel. Top. Signal Process. 15(3): 630-640 (2021) - [j32]Yannis Panagakis, Jean Kossaifi, Grigorios G. Chrysos, James Oldfield, Mihalis A. Nicolaou, Anima Anandkumar, Stefanos Zafeiriou:
Tensor Methods in Computer Vision and Deep Learning. Proc. IEEE 109(5): 863-890 (2021) - [j31]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. IEEE Robotics Autom. Lett. 6(1): 389-396 (2021) - [c124]Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue:
Deep Bayesian Quadrature Policy Optimization. AAAI 2021: 6600-6608 - [c123]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. AISTATS 2021: 3412-3420 - [c122]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting. ACC 2021: 2517-2522 - [c121]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Model Learning Predictive Control in Nonlinear Dynamical Systems. CDC 2021: 757-762 - [c120]Youngwoon Lee, Joseph J. Lim, Anima Anandkumar, Yuke Zhu:
Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization. CoRL 2021: 406-416 - [c119]Shiyi Lan, Zhiding Yu, Christopher B. Choy, Subhashree Radhakrishnan, Guilin Liu, Yuke Zhu, Larry S. Davis, Anima Anandkumar:
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision. ICCV 2021: 3386-3396 - [c118]Yoonwoo Jeong, Seokjun Ahn, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park:
Self-Calibrating Neural Radiance Fields. ICCV 2021: 5826-5834 - [c117]Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez, Zhangyang Wang, Anima Anandkumar:
Contrastive Syn-to-Real Generalization. ICLR 2021 - [c116]Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Fourier Neural Operator for Parametric Partial Differential Equations. ICLR 2021 - [c115]Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jose M. Alvarez:
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection. ICML 2021: 1463-1472 - [c114]Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar:
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. ICML 2021: 3088-3099 - [c113]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar:
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. ICML 2021: 6860-6870 - [c112]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. ICML 2021: 7301-7312 - [c111]Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu:
Fast Uncertainty Quantification for Deep Object Pose Estimation. ICRA 2021: 5200-5207 - [c110]Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu:
Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. ICRA 2021: 7540-7547 - [c109]Grigorios G. Chrysos, Jean Kossaifi, Zhiding Yu, Anima Anandkumar:
Unsupervised Controllable Generation with Self-Training. IJCNN 2021: 1-8 - [c108]Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Stephen W. Keckler, Siddharth Garg, Anima Anandkumar:
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles. IV 2021: 157-164 - [c107]Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar:
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. KDD 2021: 3576-3584 - [c106]Sahin Lale, Oguzhan Teke, Babak Hassibi, Anima Anandkumar:
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems. L4DC 2021: 651-663 - [c105]Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman:
Stable Online Control of Linear Time-Varying Systems. L4DC 2021: 742-753 - [c104]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems. L4DC 2021: 967-979 - [c103]Jing Yu, Clement Gehring, Florian Schäfer, Animashree Anandkumar:
Robust Reinforcement Learning: A Constrained Game-theoretic Approach. L4DC 2021: 1242-1254 - [c102]Aishan Liu, Xinyun Chen, Yingwei Li, Chaowei Xiao, Xun Yang, Xianglong Liu, Dawn Song, Dacheng Tao, Alan L. Yuille, Anima Anandkumar:
ADVM'21: 1st International Workshop on Adversarial Learning for Multimedia. ACM Multimedia 2021: 5686-5687 - [c101]Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang:
AugMax: Adversarial Composition of Random Augmentations for Robust Training. NeurIPS 2021: 237-250 - [c100]Zhiding Yu, Rui Huang, Wonmin Byeon, Sifei Liu, Guilin Liu, Thomas M. Breuel, Anima Anandkumar, Jan Kautz:
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation. NeurIPS 2021: 4919-4932 - [c99]Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo:
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. NeurIPS 2021: 12077-12090 - [c98]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. NeurIPS 2021: 13497-13510 - [c97]Jiachen Sun, Yulong Cao, Christopher B. Choy, Zhiding Yu, Anima Anandkumar, Zhuoqing Morley Mao, Chaowei Xiao:
Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions. NeurIPS 2021: 15498-15512 - [c96]Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro:
Long-Short Transformer: Efficient Transformers for Language and Vision. NeurIPS 2021: 17723-17736 - [c95]Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar:
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. NeurIPS 2021: 22745-22757 - [c94]Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar:
Competitive policy optimization. UAI 2021: 64-74 - [e1]Dawn Song, Dacheng Tao, Alan L. Yuille, Anima Anandkumar, Aishan Liu, Xinyun Chen, Yingwei Li, Chaowei Xiao, Xun Yang, Xianglong Liu:
ADVM '21: Proceedings of the 1st International Workshop on Adversarial Learning for Multimedia, Virtual Event, China, 20 October 2021. ACM 2021, ISBN 978-1-4503-8672-2 [contents] - [i163]Anqi Liu, Hao Liu, Tongxin Li, Saeed Karimi-Bidhendi, Yisong Yue, Anima Anandkumar:
Disentangling Observed Causal Effects from Latent Confounders using Method of Moments. CoRR abs/2101.06614 (2021) - [i162]Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar:
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. CoRR abs/2102.12596 (2021) - [i161]Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Stephen W. Keckler, Siddharth Garg, Anima Anandkumar:
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles. CoRR abs/2103.07403 (2021) - [i160]Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez, Zhangyang Wang, Anima Anandkumar:
Contrastive Syn-to-Real Generalization. CoRR abs/2104.02290 (2021) - [i159]Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose M. Alvarez:
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection. CoRR abs/2104.05702 (2021) - [i158]Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman:
Stable Online Control of Linear Time-Varying Systems. CoRR abs/2104.14134 (2021) - [i157]Shiyi Lan, Zhiding Yu, Christopher Bongsoo Choy, Subhashree Radhakrishnan, Guilin Liu, Yuke Zhu, Larry S. Davis, Anima Anandkumar:
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision. CoRR abs/2105.06464 (2021) - [i156]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar:
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. CoRR abs/2105.08692 (2021) - [i155]Zhuoran Qiao, Anders S. Christensen, Frederick R. Manby, Matthew Welborn, Anima Anandkumar, Thomas F. Miller III:
UNiTE: Unitary N-body Tensor Equivariant Network with Applications to Quantum Chemistry. CoRR abs/2105.14655 (2021) - [i154]Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo:
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. CoRR abs/2105.15203 (2021) - [i153]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. CoRR abs/2106.00136 (2021) - [i152]Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Markov Neural Operators for Learning Chaotic Systems. CoRR abs/2106.06898 (2021) - [i151]Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar:
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. CoRR abs/2106.09678 (2021) - [i150]Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, Jose M. Alvarez:
Towards Reducing Labeling Cost in Deep Object Detection. CoRR abs/2106.11921 (2021) - [i149]Jiawei Zhao, Steve Dai, Rangharajan Venkatesan, Ming-Yu Liu, Brucek Khailany, Bill Dally, Anima Anandkumar:
Low-Precision Training in Logarithmic Number System using Multiplicative Weight Update. CoRR abs/2106.13914 (2021) - [i148]Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro:
Long-Short Transformer: Efficient Transformers for Language and Vision. CoRR abs/2107.02192 (2021) - [i147]Yannis Panagakis, Jean Kossaifi, Grigorios G. Chrysos, James Oldfield, Mihalis A. Nicolaou, Anima Anandkumar, Stefanos Zafeiriou:
Tensor Methods in Computer Vision and Deep Learning. CoRR abs/2107.03436 (2021) - [i146]Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Neural Operator: Learning Maps Between Function Spaces. CoRR abs/2108.08481 (2021) - [i145]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems. CoRR abs/2108.11959 (2021) - [i144]Yoonwoo Jeong, Seokjun Ahn, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park:
Self-Calibrating Neural Radiance Fields. CoRR abs/2108.13826 (2021) - [i143]Gege Wen, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson:
U-FNO - an enhanced Fourier neural operator based-deep learning model for multiphase flow. CoRR abs/2109.03697 (2021) - [i142]Zhiqi Li, Wenhai Wang, Enze Xie, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Tong Lu, Ping Luo:
Panoptic SegFormer. CoRR abs/2109.03814 (2021) - [i141]Homanga Bharadhwaj, De-An Huang, Chaowei Xiao, Anima Anandkumar, Animesh Garg:
Auditing AI models for Verified Deployment under Semantic Specifications. CoRR abs/2109.12456 (2021) - [i140]Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman:
Stability Constrained Reinforcement Learning for Real-Time Voltage Control. CoRR abs/2109.14854 (2021) - [i139]Josiah Wong, Viktor Makoviychuk, Anima Anandkumar, Yuke Zhu:
OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation. CoRR abs/2110.00704 (2021) - [i138]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. CoRR abs/2110.10873 (2021) - [i137]Jiawei Zhao, Florian Schäfer, Anima Anandkumar:
ZerO Initialization: Initializing Residual Networks with only Zeros and Ones. CoRR abs/2110.12661 (2021) - [i136]Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang:
AugMax: Adversarial Composition of Random Augmentations for Robust Training. CoRR abs/2110.13771 (2021) - [i135]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. CoRR abs/2110.14538 (2021) - [i134]Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar:
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. CoRR abs/2111.01395 (2021) - [i133]Zongyi Li, Hongkai Zheng, Nikola B. Kovachki, David Jin, Haoxuan Chen, Burigede Liu, Kamyar Azizzadenesheli, Anima Anandkumar:
Physics-Informed Neural Operator for Learning Partial Differential Equations. CoRR abs/2111.03794 (2021) - [i132]Youngwoon Lee, Joseph J. Lim, Anima Anandkumar, Yuke Zhu:
Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization. CoRR abs/2111.07999 (2021) - [i131]Jeffrey Ma, Alistair Letcher, Florian Schäfer, Yuanyuan Shi, Anima Anandkumar:
Polymatrix Competitive Gradient Descent. CoRR abs/2111.08565 (2021) - [i130]John Guibas, Morteza Mardani, Zongyi Li, Andrew Tao, Anima Anandkumar, Bryan Catanzaro:
Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers. CoRR abs/2111.13587 (2021) - [i129]Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer:
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR abs/2112.03235 (2021) - [i128]Kevin Huang, Sahin Lale, Ugo Rosolia, Yuanyuan Shi, Anima Anandkumar:
CEM-GD: Cross-Entropy Method with Gradient Descent Planner for Model-Based Reinforcement Learning. CoRR abs/2112.07746 (2021) - [i127]Shrimai Prabhumoye, Rafal Kocielnik, Mohammad Shoeybi, Anima Anandkumar, Bryan Catanzaro:
Few-shot Instruction Prompts for Pretrained Language Models to Detect Social Biases. CoRR abs/2112.07868 (2021) - 2020
- [j30]Jean Kossaifi, Zachary C. Lipton, Arinbjörn Kolbeinsson, Aran Khanna, Tommaso Furlanello, Anima Anandkumar:
Tensor Regression Networks. J. Mach. Learn. Res. 21: 123:1-123:21 (2020) - [c93]Francesca Baldini, Animashree Anandkumar, Richard M. Murray:
Learning Pose Estimation for UAV Autonomous Navigation and Landing Using Visual-Inertial Sensor Data. ACC 2020: 2961-2966 - [c92]Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg:
Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion. CoRL 2020: 883-894 - [c91]Yang Shi, Animashree Anandkumar:
Higher-Order Count Sketch: Dimensionality Reduction that Retains Efficient Tensor Operations. DCC 2020: 394 - [c90]Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Raul Puri, Pascale Fung, Anima Anandkumar, Bryan Catanzaro:
MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models. EMNLP (1) 2020: 2831-2845 - [c89]Animashree Anandkumar:
Role of HPC in next-generation AI. HiPC 2020: xx - [c88]Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar:
Angular Visual Hardness. ICML 2020: 1637-1648 - [c87]Wuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar:
Automated Synthetic-to-Real Generalization. ICML 2020: 1746-1756 - [c86]Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar:
Semi-Supervised StyleGAN for Disentanglement Learning. ICML 2020: 7360-7369 - [c85]Florian Schäfer, Hongkai Zheng, Animashree Anandkumar:
Implicit competitive regularization in GANs. ICML 2020: 8533-8544 - [c84]Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue:
Robust Regression for Safe Exploration in Control. L4DC 2020: 608-619 - [c83]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. NeurIPS 2020 - [c82]Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar:
Neural Networks with Recurrent Generative Feedback. NeurIPS 2020 - [c81]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems. NeurIPS 2020 - [c80]Yunzhu Li, Antonio Torralba, Anima Anandkumar, Dieter Fox, Animesh Garg:
Causal Discovery in Physical Systems from Videos. NeurIPS 2020 - [c79]Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew M. Stuart, Kaushik Bhattacharya, Anima Anandkumar:
Multipole Graph Neural Operator for Parametric Partial Differential Equations. NeurIPS 2020 - [c78]Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar:
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. NeurIPS 2020 - [c77]Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar:
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning. NeurIPS 2020 - [c76]Chiyu "Max" Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar:
MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework. SC 2020: 9 - [c75]Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg:
OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation. UAI 2020: 1378-1387 - [i126]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Regret Minimization in Partially Observable Linear Quadratic Control. CoRR abs/2002.00082 (2020) - [i125]Jiahao Su, Wonmin Byeon, Furong Huang, Jan Kautz, Animashree Anandkumar:
Convolutional Tensor-Train LSTM for Spatio-temporal Learning. CoRR abs/2002.09131 (2020) - [i124]Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar:
Semi-Supervised StyleGAN for Disentanglement Learning. CoRR abs/2003.03461 (2020) - [i123]Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Neural Operator: Graph Kernel Network for Partial Differential Equations. CoRR abs/2003.03485 (2020) - [i122]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems. CoRR abs/2003.05999 (2020) - [i121]Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems. CoRR abs/2003.11227 (2020) - [i120]Majid Janzamin, Rong Ge, Jean Kossaifi, Anima Anandkumar:
Spectral Learning on Matrices and Tensors. CoRR abs/2004.07984 (2020) - [i119]Chiyu "Max" Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar:
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework. CoRR abs/2005.01463 (2020) - [i118]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. CoRR abs/2005.04374 (2020) - [i117]Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar:
Multipole Graph Neural Operator for Parametric Partial Differential Equations. CoRR abs/2006.09535 (2020) - [i116]Florian Schäfer, Anima Anandkumar, Houman Owhadi:
Competitive Mirror Descent. CoRR abs/2006.10179 (2020) - [i115]Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar:
Competitive Policy Optimization. CoRR abs/2006.10611 (2020) - [i114]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. CoRR abs/2006.14560 (2020) - [i113]Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue:
Deep Bayesian Quadrature Policy Optimization. CoRR abs/2006.15637 (2020) - [i112]Yunzhu Li, Antonio Torralba, Animashree Anandkumar, Dieter Fox, Animesh Garg:
Causal Discovery in Physical Systems from Videos. CoRR abs/2007.00631 (2020) - [i111]Wuyang Chen, Zhiding Yu, Zhangyang Wang, Anima Anandkumar:
Automated Synthetic-to-Real Generalization. CoRR abs/2007.06965 (2020) - [i110]Zhuoran Qiao, Matthew Welborn, Animashree Anandkumar, Frederick R. Manby, Thomas F. Miller III:
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features. CoRR abs/2007.08026 (2020) - [i109]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. CoRR abs/2007.08479 (2020) - [i108]Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar:
Neural Networks with Recurrent Generative Feedback. CoRR abs/2007.09200 (2020) - [i107]