conftrace_

stochastic control

43 papers

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Co-occurring keywords

optimal control (218) neural network (6616) model predictive control (174) reinforcement learning (4352) linear quadratic regulator (56) variational inference (2069) multi-agent system (1819) formal verification (284) bayesian inference (1907) policy optimization (657)

Papers

Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations AAAI 2026
Physics-Informed Representation and Learning: Control and Risk Quantification AAAI 2024
Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning AAAI 2024
Learning Discrete-Time Major-Minor Mean Field Games AAAI 2024
Approximate Control for Continuous-Time POMDPs AISTATS 2024
Soft-constrained Schrödinger Bridge: a Stochastic Control Approach AISTATS 2024
Design of observer-based finite-time control for inductively coupled power transfer system with random gain fluctuations L4DC 2024
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees NIPS 2023
Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees AAAI 2023
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms ICML 2022
Minimal Expected Regret in Linear Quadratic Control AISTATS 2022
Neural Stochastic Control NIPS 2022
Amortized Generation of Sequential Algorithmic Recourses for Black-Box Models AAAI 2022
Stability Verification in Stochastic Control Systems via Neural Network Supermartingales AAAI 2022
Solving high-dimensional parabolic PDEs using the tensor train format ICML 2021
Variational Inference MPC using Tsallis Divergence RSS 2021
Feynman-Kac Neural Network Architectures for Stochastic Control Using Second-Order FBSDE Theory L4DC 2020
Learning-based Stochastic Model Predictive Control with State-Dependent Uncertainty L4DC 2020
Dual Stochastic MPC for Systems with Parametric and Structural Uncertainty L4DC 2020
Adaptive Smoothing for Path Integral Control JMLR 2020
Reinforcement Learning in Continuous Time and Space: A Stochastic Control Approach JMLR 2020
Dynamic Control of Stochastic Evolution: A Deep Reinforcement Learning Approach to Adaptively Targeting Emergent Drug Resistance JMLR 2020
Theoretical guarantees for sampling and inference in generative models with latent diffusions COLT 2019
Stochastic Optimal Control as Approximate Input Inference CORL 2019
A Latent Variational Framework for Stochastic Optimization NIPS 2019