Kamyar Azizzadenesheli

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University of California, Irvine

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

We introduce a scheme for probabilistic hypocenter inversion with Stein ...
01/09/2021 ∙ by Jonathan D. Smith, et al. ∙ 7 ∙ share

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Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift

We study generalization under label shift in domain adaptation where the...
11/29/2020 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Fourier Neural Operator for Parametric Partial Differential Equations

The classical development of neural networks has primarily focused on le...
10/18/2020 ∙ by Zongyi Li, et al. ∙ 170 ∙ share

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Explore More and Improve Regret in Linear Quadratic Regulators

Stabilizing the unknown dynamics of a control system and minimizing regr...
07/23/2020 ∙ by Sahin Lale, et al. ∙ 27 ∙ share

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Deep Bayesian Quadrature Policy Optimization

We study the problem of obtaining accurate policy gradient estimates. Th...
06/28/2020 ∙ by Akella Ravi Tej, et al. ∙ 6 ∙ share

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Competitive Policy Optimization

A core challenge in policy optimization in competitive Markov decision p...
06/18/2020 ∙ by Manish Prajapat, et al. ∙ 16 ∙ share

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Multipole Graph Neural Operator for Parametric Partial Differential Equations

One of the main challenges in using deep learning-based methods for simu...
06/16/2020 ∙ by Zongyi Li, et al. ∙ 5 ∙ share

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

We propose MeshfreeFlowNet, a novel deep learning-based super-resolution...
05/01/2020 ∙ by Chiyu "Max" Jiang, et al. ∙ 3 ∙ share

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Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems

We study the problem of adaptive control in partially observable linear ...
03/25/2020 ∙ by Sahin Lale, et al. ∙ 4 ∙ share

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EikoNet: Solving the Eikonal equation with Deep Neural Networks

The recent deep learning revolution has created an enormous opportunity ...
03/25/2020 ∙ by Jonathan D. Smith, et al. ∙ 31 ∙ share

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

We study the problem of adaptive control in partially observable linear ...
03/12/2020 ∙ by Sahin Lale, et al. ∙ 4 ∙ share

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Neural Operator: Graph Kernel Network for Partial Differential Equations

The classical development of neural networks has been primarily for mapp...
03/07/2020 ∙ by Zongyi Li, et al. ∙ 22 ∙ share

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Regret Minimization in Partially Observable Linear Quadratic Control

We study the problem of regret minimization in partially observable line...
01/31/2020 ∙ by Sahin Lale, et al. ∙ 13 ∙ share

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Directivity Modes of Earthquake Populations with Unsupervised Learning

We present a novel approach for resolving modes of rupture directivity i...
06/30/2019 ∙ by Zachary E. Ross, et al. ∙ 0 ∙ share

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Learning Causal State Representations of Partially Observable Environments

Intelligent agents can cope with sensory-rich environments by learning t...
06/25/2019 ∙ by Amy Zhang, et al. ∙ 68 ∙ share

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Regularized Learning for Domain Adaptation under Label Shifts

We propose Regularized Learning under Label shifts (RLLS), a principled ...
03/22/2019 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Stochastic Linear Bandits with Hidden Low Rank Structure

High-dimensional representations often have a lower dimensional underlyi...
01/28/2019 ∙ by Sahin Lale, et al. ∙ 18 ∙ share

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Neural Lander: Stable Drone Landing Control using Learned Dynamics

Precise trajectory control near ground is difficult for multi-rotor dron...
11/19/2018 ∙ by Guanya Shi, et al. ∙ 0 ∙ share

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Trust Region Policy Optimization of POMDPs

We propose Generalized Trust Region Policy Optimization (GTRPO), a Reinf...
10/18/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant

Training neural networks on large datasets can be accelerated by distrib...
10/11/2018 ∙ by Jeremy Bernstein, et al. ∙ 0 ∙ share

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Sample-Efficient Deep RL with Generative Adversarial Tree Search

We propose Generative Adversarial Tree Search (GATS), a sample-efficient...
06/15/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 4 ∙ share

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Stochastic Activation Pruning for Robust Adversarial Defense

Neural networks are known to be vulnerable to adversarial examples. Care...
03/05/2018 ∙ by Guneet S. Dhillon, et al. ∙ 0 ∙ share

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signSGD: compressed optimisation for non-convex problems

Training large neural networks requires distributing learning across mul...
02/13/2018 ∙ by Jeremy Bernstein, et al. ∙ 0 ∙ share

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Efficient Exploration through Bayesian Deep Q-Networks

We propose Bayesian Deep Q-Network (BDQN), a practical Thompson sampling...
02/13/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Experimental results : Reinforcement Learning of POMDPs using Spectral Methods

We propose a new reinforcement learning algorithm for partially observab...
05/07/2017 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Reinforcement Learning in Rich-Observation MDPs using Spectral Methods

Designing effective exploration-exploitation algorithms in Markov decisi...
11/11/2016 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Reinforcement Learning of POMDPs using Spectral Methods

We propose a new reinforcement learning algorithm for partially observab...
02/25/2016 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Kamyar Azizzadenesheli

Featured Co-authors

Anima Anandkumar

Joelle Pineau

Yisong Yue

Zachary C Lipton

Mohammad Ghavamzadeh

Emma Brunskill

Alessandro Lazaric

Yu-Xiang Wang

Babak Hassibi

Prabhat

Laurent Itti

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

Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift

Fourier Neural Operator for Parametric Partial Differential Equations

Explore More and Improve Regret in Linear Quadratic Regulators

Deep Bayesian Quadrature Policy Optimization

Competitive Policy Optimization

Multipole Graph Neural Operator for Parametric Partial Differential Equations

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

Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems

EikoNet: Solving the Eikonal equation with Deep Neural Networks

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

Neural Operator: Graph Kernel Network for Partial Differential Equations

Regret Minimization in Partially Observable Linear Quadratic Control

Directivity Modes of Earthquake Populations with Unsupervised Learning

Learning Causal State Representations of Partially Observable Environments

Regularized Learning for Domain Adaptation under Label Shifts

Stochastic Linear Bandits with Hidden Low Rank Structure

Neural Lander: Stable Drone Landing Control using Learned Dynamics

Trust Region Policy Optimization of POMDPs

signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant

Sample-Efficient Deep RL with Generative Adversarial Tree Search

Stochastic Activation Pruning for Robust Adversarial Defense

signSGD: compressed optimisation for non-convex problems

Efficient Exploration through Bayesian Deep Q-Networks

Experimental results : Reinforcement Learning of POMDPs using Spectral Methods

Reinforcement Learning in Rich-Observation MDPs using Spectral Methods

Reinforcement Learning of POMDPs using Spectral Methods