| # exploration: A study of count-based exploration for deep reinforcement learning H Tang, R Houthooft, D Foote, A Stooke, OAI Xi Chen, Y Duan, ... Advances in neural information processing systems 30, 2017 | 867* | 2017 |
| Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer K Nagpal, D Foote, Y Liu, PHC Chen, E Wulczyn, F Tan, N Olson, ... NPJ digital medicine 2 (1), 48, 2019 | 434 | 2019 |
| Development and validation of a deep learning algorithm for Gleason grading of prostate cancer from biopsy specimens K Nagpal, D Foote, F Tan, Y Liu, PHC Chen, DF Steiner, N Manoj, ... JAMA oncology 6 (9), 1372-1380, 2020 | 147 | 2020 |
| Evaluation of the use of combined artificial intelligence and pathologist assessment to review and grade prostate biopsies DF Steiner, K Nagpal, R Sayres, DJ Foote, BD Wedin, A Pearce, CJ Cai, ... JAMA network open 3 (11), e2023267-e2023267, 2020 | 69 | 2020 |
| When Your AI Deceives You: Challenges with Partial Observability of Human Evaluators in Reward Learning L Lang, D Foote, S Russell, A Dragan, E Jenner, S Emmons arXiv preprint arXiv:2402.17747, 2024 | 1 | 2024 |
| AI Alignment with Changing and Influenceable Reward Functions M Carroll, D Foote, A Siththaranjan, S Russell, A Dragan ICLR 2024 Workshop: How Far Are We From AGI, 0 | | |
| Polynomial Time Approximate Solutions to Markov Decision Processes with Many Objectives D Foote, B Chu | | |
