Co-occurring keywords · papers mentioning both
Papers
Probabilistic Safety Verification of Neural Policies via Predicate Abstraction
AAAI 2026
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
NeurIPS 2023
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
NeurIPS 2023
UniFolding: Towards Sample-efficient, Scalable, and Generalizable Robotic Garment Folding
CoRL 2023
Adversarially Regularized Policy Learning Guided by Trajectory Optimization
L4DC 2022
Symbolic Distillation for Learned TCP Congestion Control
NeurIPS 2022
Compositional Reinforcement Learning from Logical Specifications
NeurIPS 2021
Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning
CoRL 2021
Enforcing robust control guarantees within neural network policies
ICLR 2021
Learning to Synthesize Programs as Interpretable and Generalizable Policies
NeurIPS 2021
Discriminative Particle Filter Reinforcement Learning for Complex Partial observations
ICLR 2020
From pixels to legs: Hierarchical learning of quadruped locomotion
CoRL 2020
Neural Network Control Policy Verification With Persistent Adversarial Perturbation
ICML 2020
Probably Approximately Correct Vision-Based Planning using Motion Primitives
CoRL 2020
Learning to Walk Via Deep Reinforcement Learning
RSS 2019
Constrained Policy Optimization
ICML 2017
Trust Region Policy Optimization
ICML 2015
Learning Complex Neural Network Policies with Trajectory Optimization
ICML 2014
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
NeurIPS 2014