| Online learning in bandits with predicted context Y Guo, Z Xu, S Murphy International Conference on Artificial Intelligence and Statistics, 2215-2223, 2024 | | 2024 |
| Contextual bandits with budgeted information reveal K Gan, E Keyvanshokooh, X Liu, S Murphy International Conference on Artificial Intelligence and Statistics, 3970-3978, 2024 | 3 | 2024 |
| Did we personalize? assessing personalization by an online reinforcement learning algorithm using resampling S Ghosh, R Kim, P Chhabria, R Dwivedi, P Klasnja, P Liao, K Zhang, ... Machine Learning, 1-37, 2024 | 6 | 2024 |
| Optimizing an adaptive digital oral health intervention for promoting oral self-care behaviors: Micro-randomized trial protocol I Nahum-Shani, ZM Greer, AL Trella, KW Zhang, SM Carpenter, ... Contemporary Clinical Trials 139, 107464, 2024 | 2 | 2024 |
| The Fallacy of Minimizing Local Regret in the Sequential Task Setting Z Xu, KW Zhang, SA Murphy arXiv preprint arXiv:2403.10946, 2024 | | 2024 |
| Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning Z Buçinca, S Swaroop, AE Paluch, SA Murphy, KZ Gajos arXiv preprint arXiv:2403.05911, 2024 | 1 | 2024 |
| reBandit: Random Effects based Online RL algorithm for Reducing Cannabis Use S Ghosh, Y Guo, PY Hung, L Coughlin, E Bonar, I Nahum-Shani, ... arXiv preprint arXiv:2402.17739, 2024 | | 2024 |
| Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials AL Trella, KW Zhang, I Nahum-Shani, V Shetty, I Yan, F Doshi-Velez, ... arXiv preprint arXiv:2402.17003, 2024 | | 2024 |
| Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology LM Collins, I Nahum-Shani, K Guastaferro, JC Strayhorn, DJ Vanness, ... Annual Review of Clinical Psychology 20, 2024 | 1 | 2024 |
| Non-Stationary Latent Auto-Regressive Bandits AL Trella, W Dempsey, F Doshi-Velez, SA Murphy arXiv preprint arXiv:2402.03110, 2024 | | 2024 |
| Online Uniform Risk Times Sampling: First Approximation Algorithms, Learning Augmentation with Full Confidence Interval Integration X Liu, K Gan, E Keyvanshokooh, S Murphy arXiv preprint arXiv:2402.01995, 2024 | 1 | 2024 |
| Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks E Nofshin, S Swaroop, W Pan, S Murphy, F Doshi-Velez arXiv preprint arXiv:2401.14923, 2024 | 1 | 2024 |
| Effect-Invariant Mechanisms for Policy Generalization S Saengkyongam, N Pfister, P Klasnja, S Murphy, J Peters Journal of Machine Learning Research 25 (34), 1-36, 2024 | | 2024 |
| Developing Message Strategies to Engage Racial and Ethnic Minority Groups in Digital Oral Self-Care Interventions: Participatory Co-Design Approach SM Carpenter, ZM Greer, R Newman, SA Murphy, V Shetty, ... JMIR Formative Research 7 (1), e49179, 2023 | 1 | 2023 |
| Causality in Goal Conditioned RL: Return to No Future? I Malenica, S Murphy NeurIPS 2023 Workshop on Goal-Conditioned Reinforcement Learning, 2023 | 1 | 2023 |
| A randomized trial of a mobile health intervention to augment cardiac rehabilitation JR Golbus, K Gupta, R Stevens, VSE Jeganathan, E Luff, J Shi, ... NPJ Digital Medicine 6 (1), 173, 2023 | 2 | 2023 |
| The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward JM Lipschitz, CK Pike, TP Hogan, SA Murphy, KE Burdick Current treatment options in psychiatry 10 (3), 119-135, 2023 | 14 | 2023 |
| Dyadic Reinforcement Learning S Li, LS Niell, SW Choi, I Nahum-Shani, G Shani, S Murphy arXiv preprint arXiv:2308.07843, 2023 | 1 | 2023 |
| Sample size considerations for micro‐randomized trials with binary proximal outcomes ER Cohn, T Qian, SA Murphy Statistics in medicine 42 (16), 2777-2796, 2023 | 3 | 2023 |
| Personalised context-aware digital health interventions: crossing boundaries between data science, geoscience and health psychology M Simons, A Ligtenberg, F Naughton, S Murphy, LM König, L Winkens European Health Psychologist 23 (3), 2023 | 1 | 2023 |
