Key papers

• A Statistical Test for the Benefits of Personalizing Interventions (2026)
  Zhaoqi Li et al.
  5.01
• Proactive Inpatient Bed Requests for Emergency Department Admissions (2026)
  QIan Cheng et al.
  5.01
• Optimal Top-$k$ Identification from Pairwise Comparisons (2026)
  Motti Goldberger et al.
  4.39
• Context-Aware Optimization of Follow-Up Intervals for Type 2 Diabetes Care Using Markov Decision Processes (2026)
  Parisa Lotfibagha et al.
  4.33
• Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning (2026)
  Yu Yang et al.
  4.27
• Bayesian Deployment Approval for Learned Landing Controllers under Finite Rollout Validation (2026)
  Fei Jiang and Lei Yang
  4.27
• Distributional Determinantal Point Process for Repulsive Clustering of Distributions (2026)
  Khai Nguyen et al.
  3.51
• Statistical Reinforcement Learning in the Real World: A Survey of Challenges and Future Directions (2026)
  Asim H. Gazi et al.
  3.17
• General Value Functions for Remaining Useful Life and Failure-Mode Prediction (2026)
  Hao Yan et al.
  2.00
• dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models (2026)
  Zhengyan Wan et al.
  1.89
• DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes (2026)
  Manrui Jiang and Jingru Huang and Yong Chen and Chen Zhang
  1.89
• Policy Learning with Observational Data: The Case of Hepatitis C Treatment for HIV/HCV Co-Infected Patients (2026)
  Rapha\"el Langevin
  1.89
• Precision Physical Activity Prescription via Reinforcement Learning for Functional Actions (2026)
  Gefei Lin et al.
  1.89
• Simulation-Based Optimisation of Batting Order and Bowling Plans in T20 Cricket (2026)
  Tinniam V Ganesh
  1.83
• Lightweight Adaptation for LLM-based Technical Service Agent: Latent Logic Augmentation and Robust Noise Reduction (2026)
  Yi Yu et al.
  1.78
• ImplicitRM: Unbiased Reward Modeling from Implicit Preference Data for LLM alignment (2026)
  Hao Wang et al.
  1.78
• Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets (2026)
  Nelson Salazar-Pena et al.
  1.72
• E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing (2025)
  Shuvom Sadhuka et al.
  1.61
• Practical considerations when designing an online learning algorithm for an app-based mHealth intervention (2025)
  Rachel T Gonzalez et al.
  1.56
• Diabetes Lifestyle Medicine Treatment Assistance Using Reinforcement Learning (2025)
  Yuhan Tang
  1.50
• Optimized Renewable Energy Planning MDP for Socially-Equitable Electricity Coverage in the US (2025)
  Riya Kinnarkar et al.
  1.44
• Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management (2025)
  Sanjay Basu et al.
  1.44
• Hybrid Adaptive Conformal Offline Reinforcement Learning for Fair Population Health Management (2025)
  Sanjay Basu et al.
  1.44
• Real-World Receptivity to Adaptive Mental Health Interventions: Findings from an In-the-Wild Study (2025)
  Nilesh Kumar Sahu et al.
  1.39
• A Robust Pipeline for Differentially Private Federated Learning on Imbalanced Clinical Data using SMOTETomek and FedProx (2025)
  Rodrigo Tertulino
  1.39
• Optimization of Activity Batching Policies in Business Processes (2025)
  Orlenys L\'opez-Pintado et al.
  1.33
• A Two-armed Bandit Framework for A/B Testing (2025)
  Jinjuan Wang et al.
  1.33
• An Identifiable Cost-Aware Causal Decision-Making Framework Using Counterfactual Reasoning (2025)
  Ruichu Cai et al.
  1.22
• Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes (2025)
  Animesh Kumar Paul and Russell Greiner
  1.11
• Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology (2020)
  Corinna Maier et al.
  —
• Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome (2021)
  Hengrui Cai et al.
  —
• GEAR: On Optimal Decision Making with Auxiliary Data (2021)
  Hengrui Cai et al.
  —
• Continuous Treatment Recommendation with Deep Survival Dose Response Function (2021)
  Jie Zhu et al.
  —
• Efficient Learning of Optimal Individualized Treatment Rules for Heteroscedastic or Misspecified Treatment-Free Effect Models (2021)
  Weibin Mo and Yufeng Liu
  —
• Jump Interval-Learning for Individualized Decision Making (2021)
  Hengrui Cai et al.
  —
• Solving the non-preemptive two queue polling model with generally distributed service and switch-over durations and Poisson arrivals as a Semi-Markov Decision Process (2021)
  Dylan Solms
  —
• Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems (2022)
  Giacomo Arcieri et al.
  —
• A Decision Making Framework for Recommended Maintenance of Road Segments (2023)
  Haoyu Sun et al.
  —
• Optimal data pooling for shared learning in maintenance operations (2023)
  Collin Drent and Melvin Drent and Geert-Jan van Houtum
  —