{"total":33,"rows":[{"id":"2403.17381","title":"Application-Driven Innovation in Machine Learning","created":"2024-03-26","cited_by_count":24,"area":null},{"id":"2211.05612","title":"Power Grid Congestion Management via Topology Optimization with AlphaZero","created":"2022-11-10","cited_by_count":20,"area":null},{"id":"2212.02397","title":"PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks","created":"2022-12-05","cited_by_count":18,"area":null},{"id":"2110.12908","title":"Learning to run a power network with trust","created":"2021-10-21","cited_by_count":17,"area":null},{"id":"2304.00765","title":"Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents","created":"2023-04-03","cited_by_count":16,"area":null},{"id":"2109.03970","title":"PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems","created":"2021-09-08","cited_by_count":14,"area":null},{"id":"2110.06324","title":"A Multi-scale Time-series Dataset with Benchmark for Machine Learning in Decarbonized Energy Grids","created":"2021-10-12","cited_by_count":11,"area":null},{"id":"2311.02129","title":"Hierarchical Reinforcement Learning for Power Network Topology Control","created":"2023-11-03","cited_by_count":11,"area":null},{"id":"2207.10330","title":"Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design","created":"2022-07-21","cited_by_count":8,"area":null},{"id":"2205.05180","title":"Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI","created":"2022-05-10","cited_by_count":6,"area":null},{"id":"2109.12073","title":"A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems","created":"2021-09-24","cited_by_count":5,"area":null},{"id":"2502.08681","title":"Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control","created":"2025-02-12","cited_by_count":5,"area":null},{"id":"2109.08512","title":"Soft Actor-Critic With Integer Actions","created":"2021-09-17","cited_by_count":3,"area":null},{"id":"2401.09640","title":"Blackout Mitigation via Physics-guided RL","created":"2024-01-17","cited_by_count":3,"area":null},{"id":"2411.09856","title":"InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma","created":"2024-11-15","cited_by_count":3,"area":null},{"id":"2501.07186","title":"Graph Neural Networks for Transmission Grid Topology Control: Busbar Information Asymmetry and Heterogeneous Representations","created":"2025-01-13","cited_by_count":2,"area":null},{"id":"2212.04069","title":"Reinforcement Learning for Resilient Power Grids","created":"2022-12-08","cited_by_count":1,"area":null},{"id":"2302.07654","title":"Reinforcement Learning Based Power Grid Day-Ahead Planning and AI-Assisted Control","created":"2023-02-15","cited_by_count":1,"area":null},{"id":"2411.18050","title":"RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors","created":"2024-11-27","cited_by_count":1,"area":null},{"id":"2505.01156","title":"Machine Learning for Physical Simulation Challenge Results and Retrospective Analysis: Power Grid Use Case","created":"2025-05-02","cited_by_count":1,"area":null},{"id":"2607.13221","title":"Audited Selective Verification for Risk-Controlled N-1 Thermal Contingency Screening under Deployment Shift","created":"2026-07-14","cited_by_count":1,"area":null},{"id":"2206.02855","title":"Efficient entity-based reinforcement learning","created":"2022-06-06","cited_by_count":0,"area":null},{"id":"2211.17013","title":"Climate Change Policy Exploration using Reinforcement Learning","created":"2022-10-23","cited_by_count":0,"area":null},{"id":"2310.02605","title":"Multi-Agent Reinforcement Learning for Power Grid Topology Optimization","created":"2023-10-04","cited_by_count":0,"area":null},{"id":"2312.06036","title":"Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions","created":"2023-12-10","cited_by_count":0,"area":null},{"id":"2401.04452","title":"AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity","created":"2024-01-09","cited_by_count":0,"area":null},{"id":"2401.13693","title":"Challenge design roadmap","created":"2024-01-15","cited_by_count":0,"area":null},{"id":"2504.13314","title":"On the Definition of Robustness and Resilience of AI Agents for Real-time Congestion Management","created":"2025-04-17","cited_by_count":0,"area":null},{"id":"2602.16063","title":"MARLEM: A Multi-Agent Reinforcement Learning Simulation Framework for Implicit Cooperation in Decentralized Local Energy Markets","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2605.12462","title":"Towards Affordable Energy: A Gymnasium Environment for Electric Utility Demand-Response Programs","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.22749","title":"Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2606.20950","title":"Power Systems Agent Benchmark: Executable Evaluation of AI Agents in Electric Power Engineering","created":"2026-06-18","cited_by_count":0,"area":null},{"id":"2610.03872","title":"Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}