{"total":241,"rows":[{"id":"2107.03342","title":"A Survey of Uncertainty in Deep Neural Networks","created":"2021-07-07","cited_by_count":680,"area":null},{"id":"2108.06266","title":"Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning","created":"2021-08-13","cited_by_count":371,"area":null},{"id":"2205.10330","title":"A Review of Safe Reinforcement Learning: Methods, Theory and Applications","created":"2022-05-20","cited_by_count":181,"area":null},{"id":"2309.05837","title":"The Safety Filter: A Unified View of Safety-Critical Control in Autonomous Systems","created":"2023-09-11","cited_by_count":88,"area":null},{"id":"2106.02684","title":"Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs","created":"2021-06-04","cited_by_count":80,"area":null},{"id":"2202.06558","title":"Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation","created":"2022-02-14","cited_by_count":69,"area":null},{"id":"2209.15090","title":"Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments","created":"2022-09-29","cited_by_count":60,"area":null},{"id":"2108.13643","title":"Learning to Synthesize Programs as Interpretable and Generalizable Policies","created":"2021-08-31","cited_by_count":59,"area":null},{"id":"2110.05415","title":"Safe Reinforcement Learning Using Robust Control Barrier Functions","created":"2021-10-11","cited_by_count":59,"area":null},{"id":"2302.03122","title":"State-wise Safe Reinforcement Learning: A Survey","created":"2023-02-06","cited_by_count":55,"area":null},{"id":"2102.01168","title":"Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges","created":"2021-01-27","cited_by_count":50,"area":null},{"id":"2105.02796","title":"Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression","created":"2021-05-06","cited_by_count":49,"area":null},{"id":"2106.09110","title":"Safe Reinforcement Learning Using Advantage-Based Intervention","created":"2021-06-16","cited_by_count":47,"area":null},{"id":"2110.00675","title":"Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview","created":"2021-10-01","cited_by_count":45,"area":null},{"id":"2206.01913","title":"Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees","created":"2022-06-04","cited_by_count":40,"area":null},{"id":"2107.12045","title":"How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review","created":"2021-07-26","cited_by_count":39,"area":null},{"id":"2108.01846","title":"Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations","created":"2021-08-04","cited_by_count":39,"area":null},{"id":"2205.14691","title":"On the Robustness of Safe Reinforcement Learning under Observational Perturbations","created":"2022-05-29","cited_by_count":38,"area":null},{"id":"2209.08025","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","created":"2022-09-16","cited_by_count":36,"area":null},{"id":"2106.06239","title":"Safe Reinforcement Learning with Linear Function Approximation","created":"2021-06-11","cited_by_count":35,"area":null},{"id":"2203.02638","title":"Safe Reinforcement Learning for Legged Locomotion","created":"2022-03-05","cited_by_count":35,"area":null},{"id":"2205.06750","title":"Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking","created":"2022-05-13","cited_by_count":34,"area":null},{"id":"2107.12931","title":"Autonomous Reinforcement Learning via Subgoal Curricula","created":"2021-07-27","cited_by_count":33,"area":null},{"id":"2112.07184","title":"Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation","created":"2021-12-14","cited_by_count":33,"area":null},{"id":"2306.12371","title":"Optimistic Active Exploration of Dynamical Systems","created":"2023-06-21","cited_by_count":32,"area":null},{"id":"2105.08881","title":"Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization","created":"2021-05-19","cited_by_count":31,"area":null},{"id":"2201.12427","title":"Towards Safe Reinforcement Learning with a Safety Editor Policy","created":"2022-01-28","cited_by_count":30,"area":null},{"id":"2210.07006","title":"Sustainable Online Reinforcement Learning for Auto-bidding","created":"2022-10-13","cited_by_count":29,"area":null},{"id":"2206.10524","title":"Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control","created":"2022-06-21","cited_by_count":28,"area":null},{"id":"2306.13867","title":"Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems","created":"2023-06-24","cited_by_count":28,"area":null},{"id":"2105.13281","title":"GoSafe: Globally Optimal Safe Robot Learning","created":"2021-05-27","cited_by_count":27,"area":null},{"id":"2105.14937","title":"Safe Pontryagin Differentiable Programming","created":"2021-05-31","cited_by_count":26,"area":null},{"id":"2112.09495","title":"Stability Verification in Stochastic Control Systems via Neural Network Supermartingales","created":"2021-12-17","cited_by_count":26,"area":null},{"id":"2305.06547","title":"Neural Lyapunov Control for Discrete-Time Systems","created":"2023-05-11","cited_by_count":23,"area":null},{"id":"2203.06126","title":"Prediction Sets Adaptive to Unknown Covariate Shift","created":"2022-03-11","cited_by_count":22,"area":null},{"id":"2112.13941","title":"Safe Reinforcement Learning with Chance-constrained Model Predictive Control","created":"2021-12-27","cited_by_count":20,"area":null},{"id":"2105.04682","title":"Value Iteration in Continuous Actions, States and Time","created":"2021-05-10","cited_by_count":18,"area":null},{"id":"2303.10506","title":"Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs","created":"2023-03-18","cited_by_count":18,"area":null},{"id":"2104.06922","title":"Safe Continuous Control with Constrained Model-Based Policy Optimization","created":"2021-04-14","cited_by_count":17,"area":null},{"id":"2109.02606","title":"Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications","created":"2021-09-06","cited_by_count":17,"area":null},{"id":"2209.13308","title":"Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction","created":"2022-09-27","cited_by_count":17,"area":null},{"id":"2301.10339","title":"AutoCost: Evolving Intrinsic Cost for Zero-violation Reinforcement Learning","created":"2023-01-24","cited_by_count":17,"area":null},{"id":"2103.14722","title":"Almost Surely Stable Deep Dynamics","created":"2021-03-26","cited_by_count":16,"area":null},{"id":"2109.03861","title":"Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems","created":"2021-09-08","cited_by_count":16,"area":null},{"id":"2112.07701","title":"Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning","created":"2021-12-14","cited_by_count":16,"area":null},{"id":"2301.01526","title":"Robust Control for Dynamical Systems With Non-Gaussian Noise via Formal Abstractions","created":"2023-01-04","cited_by_count":16,"area":null},{"id":"2203.07875","title":"Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization","created":"2022-03-15","cited_by_count":15,"area":null},{"id":"2101.05916","title":"Scalable Learning of Safety Guarantees for Autonomous Systems using Hamilton-Jacobi Reachability","created":"2021-01-15","cited_by_count":14,"area":null},{"id":"2104.09582","title":"Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach","created":"2021-04-19","cited_by_count":14,"area":null},{"id":"2112.04219","title":"Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System","created":"2021-12-08","cited_by_count":14,"area":null},{"id":"2310.09360","title":"Exact Verification of ReLU Neural Control Barrier Functions","created":"2023-10-13","cited_by_count":14,"area":null},{"id":"2312.01456","title":"Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees","created":"2023-12-03","cited_by_count":14,"area":null},{"id":"2102.12668","title":"Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach","created":"2021-02-25","cited_by_count":13,"area":null},{"id":"2110.12662","title":"Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise","created":"2021-10-25","cited_by_count":13,"area":null},{"id":"2111.03165","title":"Infinite Time Horizon Safety of Bayesian Neural Networks","created":"2021-11-04","cited_by_count":13,"area":null},{"id":"2303.01076","title":"Hallucinated Adversarial Control for Conservative Offline Policy Evaluation","created":"2023-03-02","cited_by_count":13,"area":null},{"id":"2304.04066","title":"Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approach","created":"2023-04-08","cited_by_count":13,"area":null},{"id":"2305.09793","title":"Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions","created":"2023-05-16","cited_by_count":13,"area":null},{"id":"2306.03929","title":"Finding Counterfactually Optimal Action Sequences in Continuous State Spaces","created":"2023-06-06","cited_by_count":13,"area":null},{"id":"2505.17342","title":"A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety","created":"2025-05-22","cited_by_count":13,"area":null},{"id":"2103.09230","title":"Lyapunov Barrier Policy Optimization","created":"2021-03-16","cited_by_count":12,"area":null},{"id":"2109.08947","title":"Risk-averse autonomous systems: A brief history and recent developments from the perspective of optimal control","created":"2021-09-18","cited_by_count":12,"area":null},{"id":"2112.09046","title":"Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach","created":"2021-12-16","cited_by_count":12,"area":null},{"id":"2310.15641","title":"Guaranteed Coverage Prediction Intervals with Gaussian Process Regression","created":"2023-10-24","cited_by_count":12,"area":null},{"id":"2104.11706","title":"Safe Chance Constrained Reinforcement Learning for Batch Process Control","created":"2021-04-23","cited_by_count":11,"area":null},{"id":"2201.12243","title":"Joint Differentiable Optimization and Verification for Certified Reinforcement Learning","created":"2022-01-28","cited_by_count":11,"area":null},{"id":"2203.11812","title":"Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems","created":"2022-03-22","cited_by_count":11,"area":null},{"id":"2207.10415","title":"Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning","created":"2022-07-21","cited_by_count":11,"area":null},{"id":"2210.05989","title":"Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty","created":"2022-10-12","cited_by_count":11,"area":null},{"id":"2210.06380","title":"Near-Optimal Multi-Agent Learning for Safe Coverage Control","created":"2022-10-12","cited_by_count":11,"area":null},{"id":"2302.06064","title":"Provably Safe Reinforcement Learning with Step-wise Violation Constraints","created":"2023-02-13","cited_by_count":11,"area":null},{"id":"2101.12115","title":"Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application","created":"2021-01-28","cited_by_count":10,"area":null},{"id":"2102.07716","title":"How RL Agents Behave When Their Actions Are Modified","created":"2021-02-15","cited_by_count":10,"area":null},{"id":"2102.13446","title":"Safe Distributional Reinforcement Learning","created":"2021-02-26","cited_by_count":10,"area":null},{"id":"2104.09785","title":"Model-predictive control and reinforcement learning in multi-energy system case studies","created":"2021-04-20","cited_by_count":10,"area":null},{"id":"2111.04894","title":"Safe Policy Optimization with Local Generalized Linear Function Approximations","created":"2021-11-09","cited_by_count":10,"area":null},{"id":"2112.01253","title":"Youla-REN: Learning Nonlinear Feedback Policies with Robust Stability Guarantees","created":"2021-12-02","cited_by_count":10,"area":null},{"id":"2305.16614","title":"Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings","created":"2023-05-26","cited_by_count":10,"area":null},{"id":"2312.00561","title":"A safe exploration approach to constrained Markov decision processes","created":"2023-12-01","cited_by_count":10,"area":null},{"id":"2203.07505","title":"Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems","created":"2022-03-14","cited_by_count":9,"area":null},{"id":"2310.08565","title":"Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities","created":"2023-10-12","cited_by_count":9,"area":null},{"id":"2310.08602","title":"Safe Deep Policy Adaptation","created":"2023-10-08","cited_by_count":9,"area":null},{"id":"2105.12189","title":"Robust Value Iteration for Continuous Control Tasks","created":"2021-05-25","cited_by_count":8,"area":null},{"id":"2112.03575","title":"MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance","created":"2021-12-07","cited_by_count":8,"area":null},{"id":"2307.10524","title":"Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions","created":"2023-07-20","cited_by_count":8,"area":null},{"id":"2308.14424","title":"Shielded Reinforcement Learning for Hybrid Systems","created":"2023-08-28","cited_by_count":8,"area":null},{"id":"2312.10230","title":"Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming","created":"2023-12-15","cited_by_count":8,"area":null},{"id":"2403.12732","title":"Tighter Confidence Bounds for Sequential Kernel Regression","created":"2024-03-19","cited_by_count":8,"area":null},{"id":"2101.05328","title":"Uniform Error and Posterior Variance Bounds for Gaussian Process Regression with Application to Safe Control","created":"2021-01-13","cited_by_count":7,"area":null},{"id":"2109.06689","title":"Reactive and Safe Road User Simulations using Neural Barrier Certificates","created":"2021-09-14","cited_by_count":7,"area":null},{"id":"2109.14325","title":"Improving Safety in Deep Reinforcement Learning using Unsupervised Action Planning","created":"2021-09-29","cited_by_count":7,"area":null},{"id":"2210.14492","title":"Provable Safe Reinforcement Learning with Binary Feedback","created":"2022-10-26","cited_by_count":7,"area":null},{"id":"2401.14033","title":"Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations","created":"2024-01-25","cited_by_count":7,"area":null},{"id":"2405.00871","title":"Learning to Boost the Performance of Stable Nonlinear Systems","created":"2024-05-01","cited_by_count":7,"area":null},{"id":"2104.13901","title":"Symbolic Abstractions From Data: A PAC Learning Approach","created":"2021-04-28","cited_by_count":6,"area":null},{"id":"2110.01954","title":"Continuous-Time Fitted Value Iteration for Robust Policies","created":"2021-10-05","cited_by_count":6,"area":null},{"id":"2111.07395","title":"Explicit Explore, Exploit, or Escape ($E^4$): near-optimal safety-constrained reinforcement learning in polynomial time","created":"2021-11-14","cited_by_count":6,"area":null},{"id":"2202.04849","title":"SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition","created":"2022-02-10","cited_by_count":6,"area":null},{"id":"2203.01190","title":"Model-free Neural Lyapunov Control for Safe Robot Navigation","created":"2022-03-02","cited_by_count":6,"area":null},{"id":"2204.06904","title":"Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning","created":"2022-04-14","cited_by_count":6,"area":null}],"next_cursor":"100"}