Azizzadenesheli, Kamyar

55 publications

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems 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
TMLR 2025 Enabling Automatic Differentiation with Mollified Graph Neural Operators Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
NeurIPS 2025 Guided Diffusion Sampling on Function Spaces with Applications to PDEs Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar
TMLR 2025 Mesh-Informed Neural Operator : A Transformer Generative Approach Yaozhong Shi, Zachary E Ross, Domniki Asimaki, Kamyar Azizzadenesheli
UAI 2025 Off-Policy Predictive Control with Causal Sensitivity Analysis Myrl G Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar
NeurIPS 2025 PINNs with Learnable Quadrature Sourav Pal, Kamyar Azizzadenesheli, Vikas Singh
NeurIPS 2025 Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Xiaowen Dong, Kamyar Azizzadenesheli, Pierre Vandergheynst
JMLR 2025 Score-Based Diffusion Models in Function Space 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
NeurIPS 2025 Stochastic Process Learning via Operator Flow Matching Yaozhong Shi, Zachary E Ross, Domniki Asimaki, Kamyar Azizzadenesheli
TMLR 2024 Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar
ICML 2024 Equivariant Graph Neural Operator for Modeling 3D Dynamics Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
ICMLW 2024 Fourier Neural Operator Based Surrogates for $\textrm{CO}_2$ Storage in Realistic Geologies 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
TMLR 2024 Functional Linear Regression of Cumulative Distribution Functions Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli
ICLR 2024 Guaranteed Approximation Bounds for Mixed-Precision Neural Operators Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
TMLR 2024 Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs Jean Kossaifi, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar
ICML 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
ICLRW 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
ICLRW 2024 Physics-Informed Neural Networks for Sampling Jingtong Sun, Julius Berner, Kamyar Azizzadenesheli, Anima Anandkumar
NeurIPS 2024 Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
ICLR 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
NeurIPSW 2024 Scale-Consistent Learning with Neural Operators Zongyi Li, Samuel Lanthaler, Catherine Deng, Yixuan Wang, Kamyar Azizzadenesheli, Anima Anandkumar
TMLR 2024 Sparse Contextual CDF Regression Kamyar Azizzadenesheli, William Lu, Anuran Makur, Qian Zhang
AISTATS 2024 Timing as an Action: Learning When to Observe and Act Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary Lipton
TMLR 2024 Universal Functional Regression with Neural Operator Flows Yaozhong Shi, Angela F Gao, Zachary E Ross, Kamyar Azizzadenesheli
NeurIPSW 2024 Universal Functional Regression with Neural Operator Flows Yaozhong Shi, Angela F Gao, Zachary E Ross, Kamyar Azizzadenesheli
ICML 2023 Competitive Gradient Optimization Abhijeet Vyas, Brian Bullins, Kamyar Azizzadenesheli
ICML 2023 Fast Sampling of Diffusion Models via Operator Learning Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
NeurIPS 2023 Geometry-Informed Neural Operator for Large-Scale 3D PDEs Zongyi Li, Nikola Kovachki, Chris Choy, Boyi Li, Jean Kossaifi, Shourya Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Animashree Anandkumar
JMLR 2023 Neural Operator: Learning Maps Between Function Spaces with Applications to PDEs Nikola Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
NeurIPSW 2023 Physics-Informed Neural Operators with Exact Differentiation on Arbitrary Geometries Colin White, Julius Berner, Jean Kossaifi, Mogab Elleithy, David Pitt, Daniel Leibovici, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar
TMLR 2023 U-NO: U-Shaped Neural Operators Md Ashiqur Rahman, Zachary E Ross, Kamyar Azizzadenesheli
AISTATS 2022 Off-Policy Risk Assessment for Markov Decision Processes Audrey Huang, Liu Leqi, Zachary Lipton, Kamyar Azizzadenesheli
AISTATS 2022 Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar
NeurIPSW 2022 Fast Sampling of Diffusion Models via Operator Learning Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
TMLR 2022 Generative Adversarial Neural Operators Md Ashiqur Rahman, Manuel A Florez, Anima Anandkumar, Zachary E Ross, Kamyar Azizzadenesheli
ICML 2022 Langevin Monte Carlo for Contextual Bandits Pan Xu, Hongkai Zheng, Eric V Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar
NeurIPS 2022 Learning Chaotic Dynamics in Dissipative Systems Zongyi Li, Miguel Liu-Schiaffini, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
JMLR 2022 Multi-Agent Multi-Armed Bandits with Limited Communication Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
ICML 2022 Supervised Learning with General Risk Functionals Liu Leqi, Audrey Huang, Zachary Lipton, Kamyar Azizzadenesheli
COLT 2022 Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Animashree Anandkumar, Babak Hassibi
UAI 2021 Competitive Policy Optimization Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar
AAAI 2021 Deep Bayesian Quadrature Policy Optimization Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue
L4DC 2021 Finite-Time System Identification and Adaptive Control in Autoregressive Exogenous Systems Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
ICLR 2021 Fourier Neural Operator for Parametric Partial Differential Equations Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
NeurIPS 2021 Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue
NeurIPS 2021 Off-Policy Risk Assessment in Contextual Bandits Audrey Huang, Liu Leqi, Zachary Lipton, Kamyar Azizzadenesheli
NeurIPS 2020 Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar
NeurIPS 2020 Multipole Graph Neural Operator for Parametric Partial Differential Equations Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew Stuart, Kaushik Bhattacharya, Anima Anandkumar
ICLRW 2020 Neural Operator: Graph Kernel Network for Partial Differential Equations Anima Anandkumar, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Nikola Kovachki, Zongyi Li, Burigede Liu, Andrew Stuart
ICLR 2019 Regularized Learning for Domain Adaptation Under Label Shifts Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar
ICLR 2019 signSGD with Majority Vote Is Communication Efficient and Fault Tolerant Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar
ICLR 2018 Stochastic Activation Pruning for Robust Adversarial Defense Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy D. Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar
ICML 2018 signSGD: Compressed Optimisation for Non-Convex Problems Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar
COLT 2016 Open Problem: Approximate Planning of POMDPs in the Class of Memoryless Policies Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
COLT 2016 Reinforcement Learning of POMDPs Using Spectral Methods Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar