Kamyar Azizzadenesheli

According to our database, Kamyar Azizzadenesheli authored at least 92 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Functional Linear Regression of Cumulative Distribution Functions.

Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli

Trans. Mach. Learn. Res., 2024

Sparse Contextual CDF Regression.

Kamyar Azizzadenesheli, William Lu, Anuran Makur, Qian Zhang

Trans. Mach. Learn. Res., 2024

Exploring the design space of deep-learning-based weather forecasting systems.

Shoaib Ahmed Siddiqui, Jean Kossaifi, Boris Bonev, Christopher B. Choy, Jan Kautz, David Krueger, Kamyar Azizzadenesheli

CoRR, 2024

Dynamical Measure Transport and Neural PDE Solvers for Sampling.

Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Müller, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2024

Universal Functional Regression with Neural Operator Flows.

Yaozhong Shi, Angela F. Gao, Zachary E. Ross, Kamyar Azizzadenesheli

CoRR, 2024

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs.

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

CoRR, 2024

Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction.

Ziqi Ma, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Neural Operators with Localized Integral and Differential Kernels.

Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators.

Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Timing as an Action: Learning When to Observe and Act.

Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Compactly Restrictable Metric Policy Optimization Problems.

Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue

IEEE Trans. Autom. Control., May, 2023

Dynamic Obstacle Avoidance for USVs Using Cross-Domain Deep Reinforcement Learning and Neural Network Model Predictive Controller.

Jianwen Li, Jalil Chavez-Galaviz, Kamyar Azizzadenesheli, Nina Mahmoudian

Sensors, April, 2023

U-NO: U-shaped Neural Operators.

Md Ashiqur Rahman, Zachary E. Ross, Kamyar Azizzadenesheli

Trans. Mach. Learn. Res., 2023

Rapid Seismic Waveform Modeling and Inversion With Neural Operators.

Yan Yang, Angela F. Gao, Kamyar Azizzadenesheli, Robert W. Clayton, Zachary E. Ross

IEEE Trans. Geosci. Remote. Sens., 2023

Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs.

Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

J. Mach. Learn. Res., 2023

Multi-Grid Tensorized Fourier Neural Operator for High-Resolution PDEs.

Jean Kossaifi, Nikola B. Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2023

Neural Operators for Accelerating Scientific Simulations and Design.

Kamyar Azizzadenesheli, Nikola B. Kovachki, Zongyi Li, Miguel Liu-Schiaffini, Jean Kossaifi, Anima Anandkumar

CoRR, 2023

Broadband Ground Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation.

Yaozhong Shi, Grigorios Lavrentiadis, Domniki Asimaki, Zachary E. Ross, Kamyar Azizzadenesheli

CoRR, 2023

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces.

Miguel Liu-Schiaffini, Clare E. Singer, Nikola B. Kovachki, Tapio Schneider, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2023

Speeding up Fourier Neural Operators via Mixed Precision.

Colin White, Renbo Tu, Jean Kossaifi, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2023

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, 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

CoRR, 2023

Reward Selection with Noisy Observations.

Kamyar Azizzadenesheli, Trung Dang, Aranyak Mehta, Alexandros Psomas, Qian Zhang

CoRR, 2023

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

CoRR, 2023

Geometry-Informed Neural Operator for Large-Scale 3D PDEs.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Sampling of Diffusion Models via Operator Learning.

Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the International Conference on Machine Learning, 2023

Competitive Gradient Optimization.

Abhijeet Vyas, Brian Bullins, Kamyar Azizzadenesheli

Proceedings of the International Conference on Machine Learning, 2023

KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems.

Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Thompson Sampling for Partially Observable Linear-Quadratic Control.

Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi

Proceedings of the American Control Conference, 2023

2022

Learning Dissipative Dynamics in Chaotic Systems (Datasets).

Zongyi Li, Miguel Liu-Schiaffini, Nikola Borislavov Kovachki, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

Dataset, November, 2022

Generative Adversarial Neural Operators.

Md Ashiqur Rahman, Manuel A. Florez, Anima Anandkumar, Zachary E. Ross, Kamyar Azizzadenesheli

Trans. Mach. Learn. Res., 2022

Neural-Fly enables rapid learning for agile flight in strong winds.

Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung

Sci. Robotics, 2022

Importance Weight Estimation and Generalization in Domain Adaptation Under Label Shift.

Kamyar Azizzadenesheli

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Multi-Agent Multi-Armed Bandits with Limited Communication.

Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli

J. Mach. Learn. Res., 2022

PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators.

Md Ashiqur Rahman, Jasorsi Ghosh, Hrishikesh Viswanath, Kamyar Azizzadenesheli, Aniket Bera

CoRR, 2022

Accelerating Carbon Capture and Storage Modeling using Fourier Neural Operators.

Gege Wen, Zongyi Li, Qirui Long, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson

CoRR, 2022

Thompson Sampling Achieves Õ(√T) Regret in Linear Quadratic Control.

Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi

CoRR, 2022

KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Dynamical Systems.

Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar

CoRR, 2022

Functional Linear Regression of CDFs.

Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli

CoRR, 2022

Competitive Gradient Optimization.

Abhijeet Vyas, Kamyar Azizzadenesheli

CoRR, 2022

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

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

CoRR, 2022

Learning Chaotic Dynamics in Dissipative Systems.

Zongyi Li, Miguel Liu-Schiaffini, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supervised Learning with General Risk Functionals.

Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Machine Learning, 2022

Langevin Monte Carlo for Contextual Bandits.

Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar

Proceedings of the International Conference on Machine Learning, 2022

Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control.

Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Animashree Anandkumar, Babak Hassibi

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Off-Policy Risk Assessment for Markov Decision Processes.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

EikoNet: Solving the Eikonal Equation With Deep Neural Networks.

Jonathan D. Smith, Kamyar Azizzadenesheli, Zachary E. Ross

IEEE Trans. Geosci. Remote. Sens., 2021

Physics-Informed Neural Operator for Learning Partial Differential Equations.

Zongyi Li, Hongkai Zheng, Nikola B. Kovachki, David Jin, Haoxuan Chen, Burigede Liu, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2021

U-FNO - an enhanced Fourier neural operator based-deep learning model for multiphase flow.

Gege Wen, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson

CoRR, 2021

Neural Operator: Learning Maps Between Function Spaces.

Nikola B. Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

CoRR, 2021

Seismic wave propagation and inversion with Neural Operators.

Yan Yang, Angela F. Gao, Jorge C. Castellanos, Zachary E. Ross, Kamyar Azizzadenesheli, Robert W. Clayton

CoRR, 2021

Markov Neural Operators for Learning Chaotic Systems.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

CoRR, 2021

Meta-Adaptive Nonlinear Control: Theory and Algorithms.

Guanya Shi, Kamyar Azizzadenesheli, Soon-Jo Chung, Yisong Yue

CoRR, 2021

Joint Stabilization and Regret Minimization through Switching in Systems with Actuator Redundancy.

Jafar Abbaszadeh Chekan, Kamyar Azizzadenesheli, Cedric Langbort

CoRR, 2021

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

CoRR, 2021

HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks.

Jonathan D. Smith, Zachary E. Ross, Kamyar Azizzadenesheli, Jack B. Muir

CoRR, 2021

Competitive policy optimization.

Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Meta-Adaptive Nonlinear Control: Theory and Algorithms.

Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Off-Policy Risk Assessment in Contextual Bandits.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Fourier Neural Operator for Parametric Partial Differential Equations.

Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

Proceedings of the 9th International Conference on Learning Representations, 2021

Model Learning Predictive Control in Nonlinear Dynamical Systems.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

Proceedings of the 2021 American Control Conference, 2021

Deep Bayesian Quadrature Policy Optimization.

Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Explore More and Improve Regret in Linear Quadratic Regulators.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

CoRR, 2020

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

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

CoRR, 2020

Neural Operator: Graph Kernel Network for Partial Differential Equations.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

CoRR, 2020

Regret Minimization in Partially Observable Linear Quadratic Control.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

CoRR, 2020

MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework.

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

Proceedings of the International Conference for High Performance Computing, 2020

Multipole Graph Neural Operator for Parametric Partial Differential Equations.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew M. Stuart, Kaushik Bhattacharya, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems.

Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Reinforcement Learning in Structured and Partially Observable Environments.

Kamyar Azizzadenesheli

PhD thesis, 2019

Directivity Modes of Earthquake Populations with Unsupervised Learning.

Zachary E. Ross, Daniel T. Trugman, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2019

Learning Causal State Representations of Partially Observable Environments.

Amy Zhang, Zachary C. Lipton, Luis Pineda, Kamyar Azizzadenesheli, Anima Anandkumar, Laurent Itti, Joelle Pineau, Tommaso Furlanello

CoRR, 2019

Stochastic Linear Bandits with Hidden Low Rank Structure.

Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi

CoRR, 2019

Neural Lander: Stable Drone Landing Control Using Learned Dynamics.

Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung

Proceedings of the International Conference on Robotics and Automation, 2019

signSGD with Majority Vote is Communication Efficient and Fault Tolerant.

Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the 7th International Conference on Learning Representations, 2019

Regularized Learning for Domain Adaptation under Label Shifts.

Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Trust Region Policy Optimization of POMDPs.

Kamyar Azizzadenesheli, Manish Kumar Bera, Animashree Anandkumar

CoRR, 2018

signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant.

Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar

CoRR, 2018

Sample-Efficient Deep RL with Generative Adversarial Tree Search.

Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Emma Brunskill, Zachary C. Lipton, Animashree Anandkumar

CoRR, 2018

Efficient Exploration Through Bayesian Deep Q-Networks.

Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar

Proceedings of the 2018 Information Theory and Applications Workshop, 2018

SIGNSGD: Compressed Optimisation for Non-Convex Problems.

Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar

Proceedings of the 35th International Conference on Machine Learning, 2018

Stochastic Activation Pruning for Robust Adversarial Defense.

Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar

Proceedings of the 6th International Conference on Learning Representations, 2018

Compression by the signs: distributed learning is a two-way street.

Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Experimental results : Reinforcement Learning of POMDPs using Spectral Methods.

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

CoRR, 2017

2016

Reinforcement Learning of Contextual MDPs using Spectral Methods.

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

CoRR, 2016

Reinforcement Learning of POMDP's using Spectral Methods.

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

CoRR, 2016

Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies.

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

Proceedings of the 29th Conference on Learning Theory, 2016

Reinforcement Learning of POMDPs using Spectral Methods.

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

Proceedings of the 29th Conference on Learning Theory, 2016