Kamyar Azizzadenesheli

149 papers A* 22A 6C 2Misc 1Journal 109Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation. CoRR Caifeng Zou, Yaozhong Shi, Zachary E. Ross, Robert W. Clayton, Kamyar Azizzadenesheli
2026	J	`jnl`	Large-Scale 3D Ground-Motion Synthesis with Physics-Inspired Latent Operator Flow Matching. CoRR Yaozhong Shi, Grigorios Lavrentiadis, Konstantinos Tsalouchidis, Zachary E. Ross, David McCallen, Caifeng Zou, Kamyar Azizzadenesheli, Domniki Asimaki
2025	J	`jnl`	Accelerating 3D Photoacoustic Computed Tomography with End-to-End Physics-Aware Neural Operators. CoRR 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
2025	J	`jnl`	Ambient Noise Full Waveform Inversion with Neural Operators. CoRR Caifeng Zou, Zachary E. Ross, Robert W. Clayton, Fan-Chi Lin, Kamyar Azizzadenesheli
2025	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. 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
2025	J	`jnl`	Deep Physics Prior for First Order Inverse Optimization. CoRR Haoyu Yang, Kamyar Azizzadenesheli, Haoxing Ren
2025	J	`jnl`	Enabling Automatic Differentiation with Mollified Graph Neural Operators. CoRR Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel V. Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
2025	J	`jnl`	Enabling Automatic Differentiation with Mollified Graph Neural Operators. Trans. Mach. Learn. Res. Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel V. Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
2025	J	`jnl`	Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction. CoRR Christopher B. Choy, Alexey Kamenev, Jean Kossaifi, Max Rietmann, Jan Kautz, Kamyar Azizzadenesheli
2025	J	`jnl`	Fourier Neural Operator based surrogates for CO CoRR 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
2025	J	`jnl`	Guided Diffusion Sampling on Function Spaces with Applications to PDEs. CoRR Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar
2025	J	`jnl`	Mesh-Informed Neural Operator : A Transformer Generative Approach. CoRR Yaozhong Shi, Zachary E. Ross, Domniki Asimaki, Kamyar Azizzadenesheli
2025	J	`jnl`	Mesh-Informed Neural Operator : A Transformer Generative Approach. Trans. Mach. Learn. Res. Yaozhong Shi, Zachary E. Ross, Domniki Asimaki, Kamyar Azizzadenesheli
2025	J	`jnl`	Neural Dynamic Modes: Computational Imaging of Dynamical Systems from Sparse Observations. CoRR Ali SaraerToosi, Renbo Tu, Kamyar Azizzadenesheli, Aviad Levis
2025	—	`conf`	Neural Spline Operators for Risk Quantification in Stochastic Systems. CDC Zhuoyuan Wang, Raffaele Romagnoli, Kamyar Azizzadenesheli, Yorie Nakahira
2025	J	`jnl`	Neural Spline Operators for Risk Quantification in Stochastic Systems. CoRR Zhuoyuan Wang, Raffaele Romagnoli, Kamyar Azizzadenesheli, Yorie Nakahira
2025	A	`conf`	Off-policy Predictive Control with Causal Sensitivity Analysis. UAI Myrl G. Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar
2025	J	`jnl`	Physics-informed Neural-operator Predictive Control for Drag Reduction in Turbulent Flows. CoRR Zelin Zhao, Zongyi Li, Kimia Hassibi, Kamyar Azizzadenesheli, Junchi Yan, Hyunji Jane Bae, Di Zhou, Anima Anandkumar
2025	J	`jnl`	Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning. CoRR Julius Berner, Miguel Liu-Schiaffini, Jean Kossaifi, Valentin Duruisseaux, Boris Bonev, Kamyar Azizzadenesheli, Anima Anandkumar
2025	J	`jnl`	Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks. CoRR Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Kamyar Azizzadenesheli, Xiaowen Dong, Pierre Vandergheynst
2025	J	`jnl`	Scale-Consistent Learning for Partial Differential Equations. CoRR Zongyi Li, Samuel Lanthaler, Catherine Deng, Michael Chen, Yixuan Wang, Kamyar Azizzadenesheli, Anima Anandkumar
2025	J	`jnl`	Score-Based Diffusion Models in Function Space. J. Mach. Learn. Res. 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
2025	J	`jnl`	Stochastic Process Learning via Operator Flow Matching. CoRR Yaozhong Shi, Zachary E. Ross, Domniki Asimaki, Kamyar Azizzadenesheli
2025	J	`jnl`	Ultrasound Lung Aeration Map via Physics-Aware Neural Operators. CoRR Jiayun Wang, Oleksii Ostras, Masashi Sode, Bahareh Tolooshams, Zongyi Li, Kamyar Azizzadenesheli, Gianmarco Pinton, Anima Anandkumar
2024	J	`jnl`	A Library for Learning Neural Operators. CoRR Jean Kossaifi, Nikola B. Kovachki, Zongyi Li, David Pitt, Miguel Liu-Schiaffini, Robert Joseph George, Boris Bonev, Kamyar Azizzadenesheli, Julius Berner, Anima Anandkumar
2024	J	`jnl`	Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction. CoRR Ziqi Ma, Kamyar Azizzadenesheli, Anima Anandkumar
2024	J	`jnl`	Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction. Trans. Mach. Learn. Res. Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar
2024	J	`jnl`	Dynamical Measure Transport and Neural PDE Solvers for Sampling. CoRR Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Müller, Kamyar Azizzadenesheli, Anima Anandkumar
2024	A*	`conf`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	J	`jnl`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	J	`jnl`	Exploring the design space of deep-learning-based weather forecasting systems. CoRR Shoaib Ahmed Siddiqui, Jean Kossaifi, Boris Bonev, Christopher B. Choy, Jan Kautz, David Krueger, Kamyar Azizzadenesheli
2024	J	`jnl`	Functional Linear Regression of Cumulative Distribution Functions. Trans. Mach. Learn. Res. Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli
2024	A*	`conf`	Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. ICLR Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
2024	J	`jnl`	Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs. Trans. Mach. Learn. Res. Jean Kossaifi, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar
2024	A*	`conf`	Neural Operators with Localized Integral and Differential Kernels. ICML Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
2024	J	`jnl`	Neural Operators with Localized Integral and Differential Kernels. CoRR Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
2024	A*	`conf`	Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. NeurIPS 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
2024	J	`jnl`	Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. CoRR 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
2024	A*	`conf`	Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. ICLR Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
2024	J	`jnl`	Sparse Contextual CDF Regression. Trans. Mach. Learn. Res. Kamyar Azizzadenesheli, William Lu, Anuran Makur, Qian Zhang
2024	A	`conf`	Timing as an Action: Learning When to Observe and Act. AISTATS Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton
2024	J	`jnl`	Universal Functional Regression with Neural Operator Flows. CoRR Yaozhong Shi, Angela F. Gao, Zachary E. Ross, Kamyar Azizzadenesheli
2024	J	`jnl`	Universal Functional Regression with Neural Operator Flows. Trans. Mach. Learn. Res. Yaozhong Shi, Angela F. Gao, Zachary E. Ross, Kamyar Azizzadenesheli
2023	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR 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, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, 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
2023	J	`jnl`	Broadband Ground Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation. CoRR Yaozhong Shi, Grigorios Lavrentiadis, Domniki Asimaki, Zachary E. Ross, Kamyar Azizzadenesheli
2023	J	`jnl`	Compactly Restrictable Metric Policy Optimization Problems. IEEE Trans. Autom. Control. Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue
2023	A*	`conf`	Competitive Gradient Optimization. ICML Abhijeet Vyas, Brian Bullins, Kamyar Azizzadenesheli
2023	J	`jnl`	Dynamic Obstacle Avoidance for USVs Using Cross-Domain Deep Reinforcement Learning and Neural Network Model Predictive Controller. Sensors Jianwen Li, Jalil Chavez-Galaviz, Kamyar Azizzadenesheli, Nina Mahmoudian
2023	A*	`conf`	Fast Sampling of Diffusion Models via Operator Learning. ICML Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
2023	A*	`conf`	Geometry-Informed Neural Operator for Large-Scale 3D PDEs. NeurIPS 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
2023	J	`jnl`	Geometry-Informed Neural Operator for Large-Scale 3D PDEs. CoRR Zongyi Li, Nikola Borislavov Kovachki, Christopher B. Choy, Boyi Li, Jean Kossaifi, Shourya Prakash Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Anima Anandkumar
2023	—	`conf`	KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems. CDC Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar
2023	J	`jnl`	Multi-Grid Tensorized Fourier Neural Operator for High-Resolution PDEs. CoRR Jean Kossaifi, Nikola B. Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar
2023	J	`jnl`	Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs. J. Mach. Learn. Res. Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2023	J	`jnl`	Neural Operators for Accelerating Scientific Simulations and Design. CoRR Kamyar Azizzadenesheli, Nikola B. Kovachki, Zongyi Li, Miguel Liu-Schiaffini, Jean Kossaifi, Anima Anandkumar
2023	J	`jnl`	Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. CoRR Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
2023	J	`jnl`	Rapid Seismic Waveform Modeling and Inversion With Neural Operators. IEEE Trans. Geosci. Remote. Sens. Yan Yang, Angela F. Gao, Kamyar Azizzadenesheli, Robert W. Clayton, Zachary E. Ross
2023	J	`jnl`	Reward Selection with Noisy Observations. CoRR Kamyar Azizzadenesheli, Trung Dang, Aranyak Mehta, Alexandros Psomas, Qian Zhang
2023	J	`jnl`	Score-based Diffusion Models in Function Space. CoRR 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
2023	J	`jnl`	Speeding up Fourier Neural Operators via Mixed Precision. CoRR Colin White, Renbo Tu, Jean Kossaifi, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
2023	C	`conf`	Thompson Sampling for Partially Observable Linear-Quadratic Control. ACC Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi
2023	J	`jnl`	Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces. CoRR Miguel Liu-Schiaffini, Clare E. Singer, Nikola B. Kovachki, Tapio Schneider, Kamyar Azizzadenesheli, Anima Anandkumar
2023	J	`jnl`	U-NO: U-shaped Neural Operators. Trans. Mach. Learn. Res. Md Ashiqur Rahman, Zachary E. Ross, Kamyar Azizzadenesheli
2022	J	`jnl`	Accelerating Carbon Capture and Storage Modeling using Fourier Neural Operators. CoRR Gege Wen, Zongyi Li, Qirui Long, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson
2022	J	`jnl`	Compactly Restrictable Metric Policy Optimization Problems. CoRR Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue
2022	J	`jnl`	Competitive Gradient Optimization. CoRR Abhijeet Vyas, Kamyar Azizzadenesheli
2022	J	`jnl`	Fast Sampling of Diffusion Models via Operator Learning. CoRR Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
2022	J	`jnl`	FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR 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
2022	J	`jnl`	Functional Linear Regression of CDFs. CoRR Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli
2022	J	`jnl`	Generative Adversarial Neural Operators. CoRR Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar, Zachary E. Ross, Kamyar Azizzadenesheli
2022	J	`jnl`	Generative Adversarial Neural Operators. Trans. Mach. Learn. Res. Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar, Zachary E. Ross, Kamyar Azizzadenesheli
2022	J	`jnl`	Importance Weight Estimation and Generalization in Domain Adaptation Under Label Shift. IEEE Trans. Pattern Anal. Mach. Intell. Kamyar Azizzadenesheli
2022	J	`jnl`	KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Dynamical Systems. CoRR Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar
2022	A*	`conf`	Langevin Monte Carlo for Contextual Bandits. ICML Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar
2022	J	`jnl`	Langevin Monte Carlo for Contextual Bandits. CoRR Pan Xu, Hongkai Zheng, Eric Mazumdar, Kamyar Azizzadenesheli, Anima Anandkumar
2022	A*	`conf`	Learning Chaotic Dynamics in Dissipative Systems. NeurIPS Zongyi Li, Miguel Liu-Schiaffini, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2022	J	`jnl`	Multi-Agent Multi-Armed Bandits with Limited Communication. J. Mach. Learn. Res. Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
2022	J	`jnl`	Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds. CoRR Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
2022	J	`jnl`	Neural-Fly enables rapid learning for agile flight in strong winds. Sci. Robotics Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
2022	A	`conf`	Off-Policy Risk Assessment for Markov Decision Processes. AISTATS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Off-Policy Risk Assessment in Markov Decision Processes. CoRR Audrey Huang, Liu Leqi, Zachary Chase Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators. CoRR Md Ashiqur Rahman, Jasorsi Ghosh, Hrishikesh Viswanath, Kamyar Azizzadenesheli, Aniket Bera
2022	A	`conf`	Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems. AISTATS Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar
2022	A*	`conf`	Supervised Learning with General Risk Functionals. ICML Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Supervised Learning with General Risk Functionals. CoRR Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	A*	`conf`	Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control. COLT Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Animashree Anandkumar, Babak Hassibi
2022	J	`jnl`	Thompson Sampling Achieves Õ(√T) Regret in Linear Quadratic Control. CoRR Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi
2022	J	`jnl`	U-NO: U-shaped Neural Operators. CoRR Md Ashiqur Rahman, Zachary E. Ross, Kamyar Azizzadenesheli
2021	C	`conf`	Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting. ACC Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2021	A	`conf`	Competitive policy optimization. UAI Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar
2021	A*	`conf`	Deep Bayesian Quadrature Policy Optimization. AAAI Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue
2021	J	`jnl`	EikoNet: Solving the Eikonal Equation With Deep Neural Networks. IEEE Trans. Geosci. Remote. Sens. Jonathan D. Smith, Kamyar Azizzadenesheli, Zachary E. Ross
2021	—	`conf`	Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems. L4DC Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2021	J	`jnl`	Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems. CoRR Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2021	A*	`conf`	Fourier Neural Operator for Parametric Partial Differential Equations. ICLR Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2021	J	`jnl`	HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks. CoRR Jonathan D. Smith, Zachary E. Ross, Kamyar Azizzadenesheli, Jack B. Muir
2021	J	`jnl`	Joint Stabilization and Regret Minimization through Switching in Systems with Actuator Redundancy. CoRR Jafar Abbaszadeh Chekan, Kamyar Azizzadenesheli, Cedric Langbort
2021	J	`jnl`	Markov Neural Operators for Learning Chaotic Systems. CoRR Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2021	A*	`conf`	Meta-Adaptive Nonlinear Control: Theory and Algorithms. NeurIPS Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue
2021	J	`jnl`	Meta-Adaptive Nonlinear Control: Theory and Algorithms. CoRR Guanya Shi, Kamyar Azizzadenesheli, Soon-Jo Chung, Yisong Yue
2021	—	`conf`	Model Learning Predictive Control in Nonlinear Dynamical Systems. CDC Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2021	J	`jnl`	Multi-Agent Multi-Armed Bandits with Limited Communication. CoRR Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
2021	J	`jnl`	Neural Operator: Learning Maps Between Function Spaces. CoRR Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2021	A*	`conf`	Off-Policy Risk Assessment in Contextual Bandits. NeurIPS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	Off-Policy Risk Assessment in Contextual Bandits. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	Physics-Informed Neural Operator for Learning Partial Differential Equations. CoRR Zongyi Li, Hongkai Zheng, Nikola B. Kovachki, David Jin, Haoxuan Chen, Burigede Liu, Kamyar Azizzadenesheli, Anima Anandkumar
2021	J	`jnl`	Seismic wave propagation and inversion with Neural Operators. CoRR Yan Yang, Angela F. Gao, Jorge C. Castellanos, Zachary E. Ross, Kamyar Azizzadenesheli, Robert W. Clayton
2021	J	`jnl`	U-FNO - an enhanced Fourier neural operator based-deep learning model for multiphase flow. CoRR Gege Wen, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson
2020	J	`jnl`	Competitive Policy Optimization. CoRR Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar
2020	J	`jnl`	Deep Bayesian Quadrature Policy Optimization. CoRR Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue
2020	J	`jnl`	EikoNet: Solving the Eikonal equation with Deep Neural Networks. CoRR Jonathan D. Smith, Kamyar Azizzadenesheli, Zachary E. Ross
2020	J	`jnl`	Explore More and Improve Regret in Linear Quadratic Regulators. CoRR Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2020	J	`jnl`	Fourier Neural Operator for Parametric Partial Differential Equations. CoRR Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2020	J	`jnl`	Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift. CoRR Kamyar Azizzadenesheli
2020	A*	`conf`	Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems. NeurIPS Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2020	J	`jnl`	Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems. CoRR Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2020	J	`jnl`	MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework. CoRR Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar
2020	A	`conf`	MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework. SC Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar
2020	A*	`conf`	Multipole Graph Neural Operator for Parametric Partial Differential Equations. NeurIPS Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew M. Stuart, Kaushik Bhattacharya, Anima Anandkumar
2020	J	`jnl`	Multipole Graph Neural Operator for Parametric Partial Differential Equations. CoRR Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2020	J	`jnl`	Neural Operator: Graph Kernel Network for Partial Differential Equations. CoRR Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar
2020	J	`jnl`	Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems. CoRR Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2020	J	`jnl`	Regret Minimization in Partially Observable Linear Quadratic Control. CoRR Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
2019	J	`jnl`	Directivity Modes of Earthquake Populations with Unsupervised Learning. CoRR Zachary E. Ross, Daniel T. Trugman, Kamyar Azizzadenesheli, Anima Anandkumar
2019	J	`jnl`	Learning Causal State Representations of Partially Observable Environments. CoRR Amy Zhang, Zachary C. Lipton, Luis Pineda, Kamyar Azizzadenesheli, Anima Anandkumar, Laurent Itti, Joelle Pineau, Tommaso Furlanello
2019	A*	`conf`	Neural Lander: Stable Drone Landing Control Using Learned Dynamics. ICRA Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
2019	—	`conf`	Regularized Learning for Domain Adaptation under Label Shifts. ICLR (Poster) Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar
2019	J	`jnl`	Regularized Learning for Domain Adaptation under Label Shifts. CoRR Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar
2019	—	`—`	Reinforcement Learning in Structured and Partially Observable Environments. Kamyar Azizzadenesheli
2019	J	`jnl`	Stochastic Linear Bandits with Hidden Low Rank Structure. CoRR Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi
2019	—	`conf`	signSGD with Majority Vote is Communication Efficient and Fault Tolerant. ICLR (Poster) Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar
2018	—	`conf`	Compression by the signs: distributed learning is a two-way street. ICLR (Workshop) Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar
2018	Misc	`conf`	Efficient Exploration Through Bayesian Deep Q-Networks. ITA Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	J	`jnl`	Efficient Exploration through Bayesian Deep Q-Networks. CoRR Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	J	`jnl`	Neural Lander: Stable Drone Landing Control using Learned Dynamics. CoRR Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
2018	A*	`conf`	SIGNSGD: Compressed Optimisation for Non-Convex Problems. ICML Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar
2018	J	`jnl`	Sample-Efficient Deep RL with Generative Adversarial Tree Search. CoRR Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Emma Brunskill, Zachary C. Lipton, Animashree Anandkumar
2018	—	`conf`	Stochastic Activation Pruning for Robust Adversarial Defense. ICLR (Poster) Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar
2018	J	`jnl`	Stochastic Activation Pruning for Robust Adversarial Defense. CoRR Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Anima Anandkumar
2018	J	`jnl`	Trust Region Policy Optimization of POMDPs. CoRR Kamyar Azizzadenesheli, Manish Kumar Bera, Animashree Anandkumar
2018	J	`jnl`	signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant. CoRR Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar
2018	J	`jnl`	signSGD: compressed optimisation for non-convex problems. CoRR Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar
2017	J	`jnl`	Experimental results : Reinforcement Learning of POMDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	A*	`conf`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of Contextual MDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of POMDP's using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	A*	`conf`	Reinforcement Learning of POMDPs using Spectral Methods. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar