K. Azizzadenesheli

Karthik Kashinath, Prabhat, Kamyar Azizzadenesheli, 2020, SC20: International Conference for High Performance Computing, Networking, Storage and Analysis.

TOCHASTIC ACTIVATION PRUNING FOR ROBUST ADVERSARIAL DEFENSE

Guneet Singh Dhillon, Jeremy Bernstein, K. Azizzadenesheli, 2018 .

EikoNet: Solving the Eikonal Equation With Deep Neural Networks pdf

Kamyar Azizzadenesheli, Zachary E. Ross, Jonathan D. Smith, 2020, IEEE Transactions on Geoscience and Remote Sensing.

Experimental results : Reinforcement Learning of POMDPs using Spectral Methods pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Alessandro Lazaric, 2017, ArXiv.

Multipole Graph Neural Operator for Parametric Partial Differential Equations pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Andrew Stuart, 2020, NeurIPS.

Convergence rate of sign stochastic gradient descent for non-convex functions

Kamyar Azizzadenesheli, Anima Anandkumar, Yu-Xiang Wang, 2018 .

Physics-informed machine learning: case studies for weather and climate modelling

Prabhat, H. A. Tchelepi, R. Wang, 2021, Philosophical Transactions of the Royal Society A.

Regularized Learning for Domain Adaptation under Label Shifts pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Anqi Liu, 2019, ICLR.

Meta-Adaptive Nonlinear Control: Theory and Algorithms pdf

Kamyar Azizzadenesheli, Guanya Shi, Yisong Yue, 2021, NeurIPS.

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

Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson, 2021, Advances in Water Resources.

U-NO: U-shaped Neural Operators

K. Azizzadenesheli, Z. Ross, Md Ashiqur Rahman, 2022, ArXiv.

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

K. Azizzadenesheli, Anima Anandkumar, Guanya Shi, 2022, Science Robotics.

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

K. Azizzadenesheli, Anima Anandkumar, S. Benson, 2021, Advances in Water Resources.

Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems

K. Azizzadenesheli, Anima Anandkumar, Sahin Lale, 2022, AISTATS.

Competitive Policy Optimization Supplementary material

Yisong Yue, K. Azizzadenesheli, Anima Anandkumar, 2021 .

Functional Linear Regression of CDFs

K. Azizzadenesheli, A. Makur, Qian Zhang, 2022, ArXiv.

Supervised Learning with General Risk Functionals

Zachary Chase Lipton, K. Azizzadenesheli, Liu Leqi, 2022, 2206.13648.

U-NO: U-shaped Neural Operators

K. Azizzadenesheli, Z. Ross, Md Ashiqur Rahman, 2022, ArXiv.

Competitive Gradient Optimization

K. Azizzadenesheli, Abhijeet Vyas, 2022, ICML.

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

K. Azizzadenesheli, Anima Anandkumar, A. Wierman, 2022, 2206.01704.

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

K. Azizzadenesheli, Anima Anandkumar, Sahin Lale, 2022, COLT.

Langevin Monte Carlo for Contextual Bandits

Eric V. Mazumdar, K. Azizzadenesheli, Anima Anandkumar, 2022, ICML.

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

B. Hassibi, K. Azizzadenesheli, Anima Anandkumar, 2022, ArXiv.

Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems

K. Azizzadenesheli, Anima Anandkumar, Sahin Lale, 2020, AISTATS.

Compactly Restrictable Metric Policy Optimization Problems

Victor D. Dorobantu, K. Azizzadenesheli, Yisong Yue, 2022, IEEE Transactions on Automatic Control.

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

J. B. Muir, Jonathan D. Smith, K. Azizzadenesheli, 2021, ArXiv.

Learning Dissipative Dynamics in Chaotic Systems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, 2106.06898.

Model Learning Predictive Control in Nonlinear Dynamical Systems

B. Hassibi, K. Azizzadenesheli, Anima Anandkumar, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Neural Operator: Learning Maps Between Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Off-Policy Risk Assessment for Markov Decision Processes

K. Azizzadenesheli, Liu Leqi, Z. Lipton, 2022, AISTATS.

Generative Adversarial Neural Operators

K. Azizzadenesheli, Anima Anandkumar, Z. Ross, 2022, Trans. Mach. Learn. Res..

Accelerating Carbon Capture and Storage Modeling using Fourier Neural Operators

K. Azizzadenesheli, Anima Anandkumar, S. Benson, 2022, ArXiv.

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

K. Azizzadenesheli, Aniket Bera, Md Ashiqur Rahman, 2022, ArXiv.

Accelerated full seismic waveform modeling and inversion with U-shaped Neural Operators

Angela F. Gao, K. Azizzadenesheli, R. Clayton, 2022 .

Rapid Seismic Waveform Modeling and Inversion with Universal Neural Operators

Angela F. Gao, K. Azizzadenesheli, R. Clayton, 2022 .

Fast Sampling of Diffusion Models via Operator Learning

K. Azizzadenesheli, Anima Anandkumar, Weili Nie, 2022, ArXiv.

Accelerating Time-Reversal Imaging with Neural Operators for Real-time Earthquake Locations

K. Azizzadenesheli, R. Clayton, Z. Ross, 2022, 2210.06636.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Functional Linear Regression of Cumulative Distribution Functions

Qian Zhang, K. Azizzadenesheli, Qian Zhang, 2022, 2205.14545.

Fourier Neural Operator for Parametric Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2020, ICLR.

Competitive Policy Optimization pdf

Alexander Liniger, Manish Prajapat, Kamyar Azizzadenesheli, 2020, UAI.

Reinforcement Learning in Structured and Partially Observable Environments

Kamyar Azizzadenesheli, K. Azizzadenesheli, 2019 .

Policy Gradient in Partially Observable Environments: Approximation and Convergence

Yisong Yue, K. Azizzadenesheli, Anima Anandkumar, 2018 .

Reinforcement Learning of POMDPs using Spectral Methods

Kamyar Azizzadenesheli, Anima Anandkumar, Alessandro Lazaric, 2016, COLT.

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

K. Azizzadenesheli, Anima Anandkumar, K. Kashinath, 2022, ArXiv.

A learning-based multiscale method and its application to inelastic impact problems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, 2102.07256.

Multipole Graph Neural Operator for Parametric Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2020, NeurIPS.

HypoSVI: Hypocentre inversion with Stein variational inference and physics informed neural networks

J. B. Muir, K. Azizzadenesheli, Z. Ross, 2021 .

Neural Operator: Learning Maps Between Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Importance Weight Estimation and Generalization in Domain Adaptation Under Label Shift

K. Azizzadenesheli, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Learning Causal State Representations of Partially Observable Environments pdf

Joelle Pineau, Kamyar Azizzadenesheli, Anima Anandkumar, 2019, ArXiv.

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

B. Hassibi, K. Azizzadenesheli, Anima Anandkumar, 2020, 2021 American Control Conference (ACC).

Explore More and Improve Regret in Linear Quadratic Regulators pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Sahin Lale, 2020, ArXiv.

Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems pdf

Babak Hassibi, Kamyar Azizzadenesheli, Anima Anandkumar, 2020, NeurIPS.

Regret Minimization in Partially Observable Linear Quadratic Control

B. Hassibi, K. Azizzadenesheli, Anima Anandkumar, 2020, ArXiv.

Fast Sampling of Diffusion Models via Operator Learning

K. Azizzadenesheli, Anima Anandkumar, Weili Nie, 2022, ArXiv.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Markov Neural Operators for Learning Chaotic Systems pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Kaushik Bhattacharya, 2021, ArXiv.

Neural mixture model association of seismic phases

K. Azizzadenesheli, Z. Ross, Weiqiang Zhu, 2023, 2301.02597.

Multi-Agent Multi-Armed Bandits with Limited Communication pdf

Kamyar Azizzadenesheli, Vaneet Aggarwal, Mridul Agarwal, 2021, J. Mach. Learn. Res..

Score-based Diffusion Models in Function Space

Jae Hyun Lim, Vikram S. Voleti, Nikola B. Kovachki, 2023, ArXiv.

U-NO: U-shaped Neural Operators

K. Azizzadenesheli, Z. Ross, Md Ashiqur Rahman, 2022, Trans. Mach. Learn. Res..

signSGD with Majority Vote is Communication Efficient and Fault Tolerant

Kamyar Azizzadenesheli, Anima Anandkumar, Jiawei Zhao, 2018, ICLR.

Surprising Negative Results for Generative Adversarial Tree Search

Weitang Liu, Kamyar Azizzadenesheli, Emma Brunskill, 2018, 1806.05780.

Neural Lander: Stable Drone Landing Control Using Learned Dynamics

Soon-Jo Chung, Kamyar Azizzadenesheli, Yisong Yue, 2018, 2019 International Conference on Robotics and Automation (ICRA).

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

Zachary Chase Lipton, K. Azizzadenesheli, Liu Leqi, 2021, ArXiv.

Deep Bayesian Quadrature Policy Optimization pdf

Kamyar Azizzadenesheli, Yisong Yue, Anima Anandkumar, 2020, AAAI.

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

Babak Hassibi, Kamyar Azizzadenesheli, Anima Anandkumar, 2021, L4DC.

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

Kamyar Azizzadenesheli, Anima Anandkumar, Sahin Lale, 2020, ArXiv.

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

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, J. Mach. Learn. Res..

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

K. Azizzadenesheli, N. Mahmoudian, Jianwen Li, 2023, Sensors.

Rapid Seismic Waveform Modeling and Inversion With Neural Operators

Angela F. Gao, K. Azizzadenesheli, Z. Ross, 2022, IEEE Transactions on Geoscience and Remote Sensing.

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo

Doina Precup, K. Azizzadenesheli, Anima Anandkumar, 2023, ArXiv.

Speeding up Fourier Neural Operators via Mixed Precision

K. Azizzadenesheli, Anima Anandkumar, Gennady Pekhimenko, 2023, ArXiv.

Off-Policy Risk Assessment in Contextual Bandits

Zachary Chase Lipton, K. Azizzadenesheli, Liu Leqi, 2021, NeurIPS.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ACM / IMS Journal of Data Science.

Reinforcement Learning in Rich-Observation MDPs using Spectral Methods

Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar, 2016, 1611.03907.

Fast Sampling of Diffusion Models via Operator Learning

K. Azizzadenesheli, Anima Anandkumar, Weili Nie, 2022, ICML.

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, ArXiv.

Stochastic Linear Bandits with Hidden Low Rank Structure pdf

Babak Hassibi, Kamyar Azizzadenesheli, Anima Anandkumar, 2019, ArXiv.

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, arXiv.org.

Trust Region Policy Optimization for POMDPs pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Manish Kumar Bera, 2018, 1810.07900.

Joint Stabilization and Regret Minimization through Switching in Over-Actuated Systems

Jafar Abbaszadeh Chekan, K. Azizzadenesheli, Cédric Langbort, 2021, IFAC-PapersOnLine.

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

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, ArXiv.

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

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, NeurIPS.

Speeding up Fourier Neural Operators via Mixed Precision

K. Azizzadenesheli, Anima Anandkumar, Gennady Pekhimenko, 2023, ArXiv.

Real-time High-resolution CO2 Geological Storage Prediction using Nested Fourier Neural Operators

K. Azizzadenesheli, Anima Anandkumar, Zong-Yi Li, 2022, Energy & Environmental Science.

Physics-Informed Neural Operators with Exact Diﬀerentiation on Arbitrary Geometries

Zongyi Li, K. Azizzadenesheli, Colin White, 2022 .

Deep Neural Helmholtz Operators for 3D Elastic Wave Propagation and Inversion

K. Azizzadenesheli, Caifeng Zou, Zachary E. Ross, 2023, 2311.09608.

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

K. Azizzadenesheli, D. Asimaki, Grigorios Lavrentiadis, 2023, ArXiv.

Learning Chaotic Dynamics in Dissipative Systems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2022, NeurIPS.

Directivity Modes of Earthquake Populations with Unsupervised Learning pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Zachary E. Ross, 2019, Journal of Geophysical Research: Solid Earth.

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

Prabhat, Mustafa A. Mustafa, K. Azizzadenesheli, 2020, SC20: International Conference for High Performance Computing, Networking, Storage and Analysis.

Equivariant Graph Neural Operator for Modeling 3D Dynamics

J. Leskovec, K. Azizzadenesheli, Jean Kossaifi, 2024, ArXiv.

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, ArXiv.

Timing as an Action: Learning When to Observe and Act

Zachary Chase Lipton, K. Azizzadenesheli, David Benjamin Childers, 2024, AISTATS.

Neural Operator: Learning Maps Between Function Spaces pdf

Kamyar Azizzadenesheli, Nikola Kovachki, Nikola B. Kovachki, 2021, arXiv.org.

Universal Functional Regression with Neural Operator Flows

Angela F. Gao, K. Azizzadenesheli, Zachary E. Ross, 2024, ArXiv.

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs

K. Azizzadenesheli, Jean Kossaifi, Zong-Yi Li, 2024, ArXiv.