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Dynamic Social Media Monitoring for Fast-Evolving Online Discussions

Feb 24, 2021
Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar

* Preprint, Under Review 

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Disentangling Observed Causal Effects from Latent Confounders using Method of Moments

Jan 17, 2021
Anqi Liu, Hao Liu, Tongxin Li, Saeed Karimi-Bidhendi, Yisong Yue, Anima Anandkumar


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Stability and Identification of Random Asynchronous Linear Time-Invariant Systems

Dec 08, 2020
Sahin Lale, Oguzhan Teke, Babak Hassibi, Anima Anandkumar


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Fourier Neural Operator for Parametric Partial Differential Equations

Oct 18, 2020
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar


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Distributionally Robust Learning for Unsupervised Domain Adaptation

Oct 08, 2020
Haoxuan Wang, Anqi Liu, Zhiding Yu, Yisong Yue, Anima Anandkumar

* Preprint 

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MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models

Oct 02, 2020
Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Raul Puri, Pascale Fung, Anima Anandkumar, Bryan Catanzaro

* Accepted in EMNLP 2020 main conference 

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OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation

Aug 17, 2020
Hongyu Ren, Yuke Zhu, Jure Leskovec, Anima Anandkumar, Animesh Garg

* UAI 2020 

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Explore More and Improve Regret in Linear Quadratic Regulators

Jul 23, 2020
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar


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Unsupervised Controllable Generation with Self-Training

Jul 17, 2020
Grigorios G Chrysos, Jean Kossaifi, Zhiding Yu, Anima Anandkumar


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Neural Networks with Recurrent Generative Feedback

Jul 17, 2020
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar


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Automated Synthetic-to-Real Generalization

Jul 14, 2020
Wuyang Chen, Zhiding Yu, Zhangyang Wang, Anima Anandkumar

* Accepted to ICML 2020 

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Deep Bayesian Quadrature Policy Optimization

Jun 28, 2020
Akella Ravi Tej, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue

* Code available at https://github.com/Akella17/Deep-Bayesian-Quadrature-Policy-Optimization 

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Learning compositional functions via multiplicative weight updates

Jun 25, 2020
Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue


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Competitive Policy Optimization

Jun 18, 2020
Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar

* 11 pages main paper, 6 pages references, and 31 pages appendix. 14 figures 

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Competitive Mirror Descent

Jun 17, 2020
Florian Schäfer, Anima Anandkumar, Houman Owhadi

* The code used to produce the numerical experiments can be found under https://github.com/f-t-s/CMD 

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Multipole Graph Neural Operator for Parametric Partial Differential Equations

Jun 16, 2020
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar


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Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems

May 09, 2020
Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung

* Submitted to RA-L 2020 

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MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

May 01, 2020
Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar

* Supplementary Video: https://youtu.be/mjqwPch9gDo 

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Spectral Learning on Matrices and Tensors

Apr 16, 2020
Majid Janzamin, Rong Ge, Jean Kossaifi, Anima Anandkumar

* Foundations and Trends in Machine Learning: Vol. 12: No. 5-6, pp 393-536 (2019) 

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Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems

Mar 25, 2020
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar


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Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems

Mar 12, 2020
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar


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Regret Minimization in Partially Observable Linear Quadratic Control

Mar 08, 2020
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar


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Neural Operator: Graph Kernel Network for Partial Differential Equations

Mar 07, 2020
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar


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Semi-Supervised StyleGAN for Disentanglement Learning

Mar 06, 2020
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debhath, Anjul Patney, Ankit B. Patel, Anima Anandkumar

* 20 pages, 4 tables, 18 figures 

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Angular Visual Hardness

Jan 04, 2020
Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Jan Kautz, Anima Anandkumar

* Tech Report (24 pages) 

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InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers

Dec 09, 2019
Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar

* 17 pages, 14 figures, 2 tables 

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Triply Robust Off-Policy Evaluation

Nov 16, 2019
Anqi Liu, Hao Liu, Anima Anandkumar, Yisong Yue

* Preliminary Work 

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Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly-Evolving Online Debates

Nov 16, 2019
Anqi Liu, Maya Srikanth, Nicholas Adams-Cohen, R. Michael Alvarez, Anima Anandkumar

* AI for Social Good workshop at NeurIPS (2019) 

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