| Optimization methods for interpretable differentiable decision trees applied to reinforcement learning A Silva, M Gombolay, T Killian, I Jimenez, SH Son International conference on artificial intelligence and statistics, 1855-1865, 2020 | 147* | 2020 |
| Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes TW Killian, S Daulton, F Doshi-Velez, G Konidaris Advances in Neural Information Processing Systems, 6251-6262, 2017 | 127 | 2017 |
| Medical dead-ends and learning to identify high-risk states and treatments M Fatemi, TW Killian, J Subramanian, M Ghassemi Advances in Neural Information Processing Systems 34, 4856-4870, 2021 | 43 | 2021 |
| An empirical study of representation learning for reinforcement learning in healthcare TW Killian, H Zhang, J Subramanian, M Fatemi, M Ghassemi Proceedings of the Machine Learning for Health NeurIPS Workshop 136, 139-160, 2020 | 37 | 2020 |
| Direct Policy Transfer with Hidden Parameter Markov Decision Processes J Yao, TW Killian, G Konidaris, F Doshi-Velez Lifelong Learning: A Reinforcement Learning Approach Workshop at FAIM 2018, 2018 | 31* | 2018 |
| Counterfactually guided policy transfer in clinical settings TW Killian, M Ghassemi, S Joshi Conference on Health, Inference, and Learning, 5-31, 2022 | 12 | 2022 |
| Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes T Killian, G Konidaris, F Doshi-Velez arXiv preprint arXiv:1612.00475, 2016 | 12 | 2016 |
| Multiple sclerosis severity classification from clinical text AD Costa, S Denkovski, M Malyska, SY Moon, B Rufino, Z Yang, T Killian, ... arXiv preprint arXiv:2010.15316, 2020 | 11 | 2020 |
| Rebound and jet formation of a fluid-filled sphere TW Killian, RA Klaus, TT Truscott Physics of Fluids 24 (12), 2012 | 11 | 2012 |
| Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning TW Killian, S Parbhoo, M Ghassemi Transactions on Machine Learning Research, 2023 | 8 | 2023 |
| Kernelized capsule networks T Killian, J Goodwin, O Brown, SH Son arXiv preprint arXiv:1906.03164, 2019 | 5 | 2019 |
| White-box adversarial policies in deep reinforcement learning S Casper, T Killian, G Kreiman, D Hadfield-Menell arXiv preprint arXiv:2209.02167, 2022 | 3 | 2022 |
| Machine learning for health (ml4h) 2022 A Parziale, M Agrawal, S Tang, K Severson, L Oala, A Subbaswamy, ... Machine Learning for Health, 1-11, 2022 | 2 | 2022 |
| Red teaming with mind reading: White-box adversarial policies against rl agents S Casper, T Killian, G Kreiman, D Hadfield-Menell arXiv preprint arXiv:2209.02167, 2022 | 1 | 2022 |
| Self healing: solid spheres impacting soap bubbles T Killian, J Bryson, J Huey, JC Bird, JC Nave, T Truscott APS Division of Fluid Dynamics Meeting Abstracts, R4. 005, 2012 | 1* | 2012 |
| Continuous Time Evidential Distributions for Irregular Time Series TW Killian, H Zhang, T Hartvigsen, AP Amini arXiv preprint arXiv:2307.13503, 2023 | | 2023 |
| Systems and methods for detection of concealed threats MA Deangelus, J Goodwin, N Kaushik, A Opipari, T Killian US Patent App. 17/219,837, 2022 | | 2022 |
| Learning Robust Representations for Automatic Target Recognition JA Goodwin, OM Brown, TW Killian, SH Son arXiv preprint arXiv:1811.10714, 2018 | | 2018 |
| Harnessing sloshing as a passive dampener T Killian, R Klaus, T Truscott Bulletin of the American Physical Society 56, 2011 | | 2011 |
| TWK Test submission TW Killian I Can't Believe It's Not Better Workshop: Failure Modes of Sequential …, 0 | | |
Dr. Marzyeh GhassemiAssociate Professor, EECS/IMES, MIT在 mit.edu 的电子邮件经过验证
