{"total":91,"rows":[{"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":"2110.02085","title":"Enhancing Computational Fluid Dynamics with Machine Learning","created":"2021-10-05","cited_by_count":138,"area":null},{"id":"2101.05265","title":"Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning","created":"2021-01-13","cited_by_count":123,"area":null},{"id":"2103.02142","title":"Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control","created":"2021-03-03","cited_by_count":77,"area":null},{"id":"2109.06325","title":"safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics","created":"2021-09-13","cited_by_count":50,"area":null},{"id":"2403.14864","title":"Learning Quadruped Locomotion Using Differentiable Simulation","created":"2024-03-21","cited_by_count":32,"area":null},{"id":"2303.15832","title":"The transformative potential of machine learning for experiments in fluid mechanics","created":"2023-03-28","cited_by_count":27,"area":null},{"id":"2206.01463","title":"Safety Certification for Stochastic Systems via Neural Barrier Functions","created":"2022-06-03","cited_by_count":22,"area":null},{"id":"2104.01120","title":"Linear Systems can be Hard to Learn","created":"2021-04-02","cited_by_count":20,"area":null},{"id":"2109.05439","title":"Concave Utility Reinforcement Learning with Zero-Constraint Violations","created":"2021-09-12","cited_by_count":19,"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":"2101.01041","title":"Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity","created":"2021-01-04","cited_by_count":15,"area":null},{"id":"2103.12726","title":"Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning","created":"2021-03-23","cited_by_count":15,"area":null},{"id":"2102.05242","title":"Patterns, predictions, and actions: A story about machine learning","created":"2021-02-10","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":"2209.03859","title":"A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning","created":"2022-09-08","cited_by_count":14,"area":null},{"id":"2308.04428","title":"Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data","created":"2023-08-08","cited_by_count":13,"area":null},{"id":"2309.11470","title":"Model-free tracking control of complex dynamical trajectories with machine learning","created":"2023-09-20","cited_by_count":13,"area":null},{"id":"2201.01680","title":"Regret Lower Bounds for Learning Linear Quadratic Gaussian Systems","created":"2022-01-05","cited_by_count":11,"area":null},{"id":"2202.04097","title":"Turnpike in optimal control of PDEs, ResNets, and beyond","created":"2022-02-08","cited_by_count":11,"area":null},{"id":"2205.14035","title":"Learning to Control Linear Systems can be Hard","created":"2022-05-27","cited_by_count":11,"area":null},{"id":"2301.12624","title":"Learning the Kalman Filter with Fine-Grained Sample Complexity","created":"2023-01-30","cited_by_count":9,"area":null},{"id":"2206.08520","title":"Thompson Sampling Achieves $\\tilde O(\\sqrt{T})$ Regret in Linear Quadratic Control","created":"2022-06-17","cited_by_count":8,"area":null},{"id":"2401.13836","title":"Machine learning for industrial sensing and control: A survey and practical perspective","created":"2024-01-24","cited_by_count":8,"area":null},{"id":"2201.07372","title":"Prospective Learning: Principled Extrapolation to the Future","created":"2022-01-19","cited_by_count":6,"area":null},{"id":"2202.11296","title":"Reinforcement Learning in Practice: Opportunities and Challenges","created":"2022-02-23","cited_by_count":6,"area":null},{"id":"2202.11664","title":"Comparative analysis of machine learning methods for active flow control","created":"2022-02-23","cited_by_count":6,"area":null},{"id":"2203.12864","title":"Kullback-Leibler control for discrete-time nonlinear systems on continuous spaces","created":"2022-03-24","cited_by_count":6,"area":null},{"id":"2206.01341","title":"Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control","created":"2022-06-02","cited_by_count":6,"area":null},{"id":"2209.11123","title":"Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey","created":"2022-09-22","cited_by_count":6,"area":null},{"id":"2210.04810","title":"Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies","created":"2022-10-10","cited_by_count":6,"area":null},{"id":"2311.18736","title":"Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms","created":"2023-11-30","cited_by_count":6,"area":null},{"id":"2102.08792","title":"Chance-Constrained Active Inference","created":"2021-02-17","cited_by_count":5,"area":null},{"id":"2105.12545","title":"Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement Learning","created":"2021-05-26","cited_by_count":5,"area":null},{"id":"2106.10516","title":"DiffLoop: Tuning PID controllers by differentiating through the feedback loop","created":"2021-06-19","cited_by_count":5,"area":null},{"id":"2206.01704","title":"KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Dynamical Systems","created":"2022-06-03","cited_by_count":5,"area":null},{"id":"2112.06018","title":"Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control","created":"2021-12-11","cited_by_count":4,"area":null},{"id":"2209.01083","title":"When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development","created":"2022-09-02","cited_by_count":4,"area":null},{"id":"2210.11245","title":"Neural ODEs as Feedback Policies for Nonlinear Optimal Control","created":"2022-10-20","cited_by_count":4,"area":null},{"id":"2309.04831","title":"Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs","created":"2023-09-09","cited_by_count":4,"area":null},{"id":"2406.00826","title":"Policy Verification in Stochastic Dynamical Systems Using Logarithmic Neural Certificates","created":"2024-06-02","cited_by_count":4,"area":null},{"id":"2105.06577","title":"Online Algorithms and Policies Using Adaptive and Machine Learning Approaches","created":"2021-05-13","cited_by_count":3,"area":null},{"id":"2109.14675","title":"Data Sharing and Compression for Cooperative Networked Control","created":"2021-09-29","cited_by_count":3,"area":null},{"id":"2207.14419","title":"Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions","created":"2022-07-29","cited_by_count":3,"area":null},{"id":"2301.05089","title":"Approximate Information States for Worst-Case Control and Learning in Uncertain Systems","created":"2023-01-12","cited_by_count":3,"area":null},{"id":"2507.23330","title":"AI Must not be Fully Autonomous","created":"2025-07-31","cited_by_count":3,"area":null},{"id":"2103.08241","title":"Reinforcement Learning with Algorithms from Probabilistic Structure Estimation","created":"2021-03-15","cited_by_count":2,"area":null},{"id":"2105.02656","title":"A Reinforcement Learning-based Economic Model Predictive Control Framework for Autonomous Operation of Chemical Reactors","created":"2021-05-06","cited_by_count":2,"area":null},{"id":"2109.10303","title":"Computing Complexity-aware Plans Using Kolmogorov Complexity","created":"2021-09-21","cited_by_count":2,"area":null},{"id":"2110.08307","title":"GrowSpace: Learning How to Shape Plants","created":"2021-10-15","cited_by_count":2,"area":null},{"id":"2202.07808","title":"Policy Learning and Evaluation with Randomized Quasi-Monte Carlo","created":"2022-02-16","cited_by_count":2,"area":null},{"id":"2305.01124","title":"Human adaptation to adaptive machines converges to game-theoretic equilibria","created":"2023-05-01","cited_by_count":2,"area":null},{"id":"2306.04836","title":"$K$-Nearest-Neighbor Resampling for Off-Policy Evaluation in Stochastic Control","created":"2023-06-07","cited_by_count":2,"area":null},{"id":"2309.00730","title":"Tempestas ex machina: A review of machine learning methods for wavefront control","created":"2023-09-01","cited_by_count":2,"area":null},{"id":"2505.13567","title":"Learning Dynamics of RNNs in Closed-Loop Environments","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2507.04712","title":"Mutual Information Optimal Control of Discrete-Time Linear Systems","created":"2025-07-07","cited_by_count":2,"area":null},{"id":"2601.05637","title":"GenCtrl -- A Formal Controllability Toolkit for Generative Models","created":"2026-01-09","cited_by_count":2,"area":null},{"id":"2206.13714","title":"Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse","created":"2022-06-28","cited_by_count":1,"area":null},{"id":"2212.01371","title":"Adaptive Robust Model Predictive Control via Uncertainty Cancellation","created":"2022-12-02","cited_by_count":1,"area":null},{"id":"2301.07876","title":"Suboptimality analysis of receding horizon quadratic control with unknown linear systems and its applications in learning-based control","created":"2023-01-19","cited_by_count":1,"area":null},{"id":"2303.08115","title":"Human-Inspired Framework to Accelerate Reinforcement Learning","created":"2023-02-28","cited_by_count":1,"area":null},{"id":"2303.13657","title":"Policy Evaluation in Distributional LQR","created":"2023-03-23","cited_by_count":1,"area":null},{"id":"2403.01005","title":"Policy Optimization for PDE Control with a Warm Start","created":"2024-03-01","cited_by_count":1,"area":null},{"id":"2502.00443","title":"Model-Free Predictive Control: Introductory Algebraic Calculations, and a Comparison with HEOL and ANNs","created":"2025-02-01","cited_by_count":1,"area":null},{"id":"2502.17693","title":"Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse","created":"2025-02-24","cited_by_count":1,"area":null},{"id":"2512.05765","title":"AGI Requires a Coordination Layer on Top of Pattern Repositories","created":"2025-12-05","cited_by_count":1,"area":null},{"id":"2607.01819","title":"Koopman operator theory: fundamentals, control, and applications","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2101.01178","title":"Advances in Electron Microscopy with Deep Learning","created":"2021-01-04","cited_by_count":0,"area":null},{"id":"2103.04910","title":"A Crash Course on Reinforcement Learning","created":"2021-03-08","cited_by_count":0,"area":null},{"id":"2106.00343","title":"Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding","created":"2021-06-01","cited_by_count":0,"area":null},{"id":"2109.14811","title":"Surveillance Evasion Through Bayesian Reinforcement Learning","created":"2021-09-30","cited_by_count":0,"area":null},{"id":"2202.05799","title":"Rate-matching the regret lower-bound in the linear quadratic regulator with unknown dynamics","created":"2022-02-11","cited_by_count":0,"area":null},{"id":"2208.08087","title":"Autonomous Resource Management in Construction Companies Using Deep Reinforcement Learning Based on IoT","created":"2022-08-17","cited_by_count":0,"area":null},{"id":"2210.00770","title":"Accelerate Reinforcement Learning with PID Controllers in the Pendulum Simulations","created":"2022-10-03","cited_by_count":0,"area":null},{"id":"2211.03136","title":"Design Process is a Reinforcement Learning Problem","created":"2022-11-06","cited_by_count":0,"area":null},{"id":"2212.12329","title":"Approaching Globally Optimal Energy Efficiency in Interference Networks via Machine Learning","created":"2022-11-25","cited_by_count":0,"area":null},{"id":"2306.06402","title":"A Single-Loop Deep Actor-Critic Algorithm for Constrained Reinforcement Learning with Provable Convergence","created":"2023-06-10","cited_by_count":0,"area":null},{"id":"2309.09205","title":"MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference","created":"2023-09-17","cited_by_count":0,"area":null},{"id":"2309.10831","title":"Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach","created":"2023-09-18","cited_by_count":0,"area":null},{"id":"2310.04842","title":"Sub-linear Regret in Adaptive Model Predictive Control","created":"2023-10-07","cited_by_count":0,"area":null},{"id":"2311.07563","title":"Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics","created":"2023-11-13","cited_by_count":0,"area":null},{"id":"2312.09773","title":"In vivo learning-based control of microbial populations density in bioreactors","created":"2023-12-15","cited_by_count":0,"area":null},{"id":"2501.08626","title":"A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game","created":"2025-01-15","cited_by_count":0,"area":null},{"id":"2501.17256","title":"Increasing Information for Model Predictive Control with Semi-Markov Decision Processes","created":"2025-01-28","cited_by_count":0,"area":null},{"id":"2507.04356","title":"Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations","created":"2025-07-06","cited_by_count":0,"area":null},{"id":"2508.17142","title":"Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis","created":"2025-08-23","cited_by_count":0,"area":null},{"id":"2604.14484","title":"Behavior Cloning Under PD Control: A Finite-Horizon Theory of Gain-Dependent Error Amplification","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2606.28281","title":"PAC-Bayesian Certificates for Quadratic Closed-Loop Control","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2608.13625","title":"Reward Machines for Signal Temporal Logic","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2609.06197","title":"Algorithmic Optimality Guarantees for Nonsmooth $H_\\infty$ Output-Feedback Policy Search","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2610.05689","title":"Toward AI Trustworthiness: Finding Analytically Proven Forward-Invariant Sets for AI-Controlled Systems","created":"2026-10-05","cited_by_count":0,"area":null}],"next_cursor":null}