Kamyar Azizzadenesheli
34 papers · 2016–2026 · 10 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (69) π Conference Polyglot Β· Gold π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Dynamic Duo
(16)
π
Triple Crown
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
π
Conference Pioneer
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Renaissance Researcher
(6)
ποΈ
Keyword Collector
(161)
Venues
Top co-authors
Research topics
Machine Learning
(25)
Artificial Intelligence
(15)
Optimization & Theory
(14)
Reinforcement Learning
(12)
Learning Types Β· Machine Learning
(12)
Deep Learning
(11)
Methods
(11)
Core AI
(10)
Mathematics & Optimization
(9)
Optimization
(8)
Architectures
(7)
Core Methods
(6)
Learning Paradigms
(4)
Applications
(3)
Learning Types Β· Deep Learning
(3)
Keywords
regret bound
(8)
partial differential equation
(5)
fourier neural operator
(4)
adaptive control
(4)
thompson sampling
(3)
neural operator
(3)
contextual bandit
(2)
diffusion model
(2)
risk assessment
(2)
partial observability
(2)
generalization bound
(2)
model-based reinforcement learning
(2)
fourier transform
(2)
gradient compression
(2)
off-policy evaluation
(2)
system identification
(2)
distributed optimization
(2)
markov chain monte carlo
(2)
distributed learning
(2)
function space
(2)
Papers
Reward Selection with Noisy Observations
ALT 2026
Off-policy Predictive Control with Causal Sensitivity Analysis
UAI 2025
Score-Based Diffusion Models in Function Space
JMLR 2025
Equivariant Graph Neural Operator for Modeling 3D Dynamics
ICML 2024
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
ICLR 2024
Neural Operators with Localized Integral and Differential Kernels
ICML 2024
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
NeurIPS 2024
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
ICLR 2024
Timing as an Action: Learning When to Observe and Act
AISTATS 2024
Competitive Gradient Optimization
ICML 2023
Fast Sampling of Diffusion Models via Operator Learning
ICML 2023
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
NeurIPS 2023
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs
JMLR 2023
Langevin Monte Carlo for Contextual Bandits
ICML 2022
Learning Chaotic Dynamics in Dissipative Systems
NeurIPS 2022
Multi-Agent Multi-Armed Bandits with Limited Communication
JMLR 2022
Off-Policy Risk Assessment for Markov Decision Processes
AISTATS 2022
Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems
AISTATS 2022
Supervised Learning with General Risk Functionals
ICML 2022
Thompson Sampling Achieves OΜ(βT) Regret in Linear Quadratic Control
COLT 2022
Competitive policy optimization
UAI 2021
Deep Bayesian Quadrature Policy Optimization
AAAI 2021
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems
L4DC 2021
Fourier Neural Operator for Parametric Partial Differential Equations
ICLR 2021
Meta-Adaptive Nonlinear Control: Theory and Algorithms
NeurIPS 2021
Off-Policy Risk Assessment in Contextual Bandits
NeurIPS 2021
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
NeurIPS 2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations
NeurIPS 2020
Regularized Learning for Domain Adaptation under Label Shifts
ICLR 2019
signSGD with Majority Vote is Communication Efficient and Fault Tolerant
ICLR 2019
signSGD: Compressed Optimisation for Non-Convex Problems
ICML 2018
Stochastic Activation Pruning for Robust Adversarial Defense
ICLR 2018
Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies
COLT 2016
Reinforcement Learning of POMDPs using Spectral Methods
COLT 2016