Omer Gottesman
Cited by
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Guidelines for reinforcement learning in healthcare
O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ...
Nature medicine 25 (1), 16-18, 2019
Science with a wide-field UV transient explorer
I Sagiv, A Gal-Yam, EO Ofek, E Waxman, O Aharonson, SR Kulkarni, ...
The Astronomical Journal 147 (4), 79, 2014
Evaluating reinforcement learning algorithms in observational health settings
O Gottesman, F Johansson, J Meier, J Dent, D Lee, S Srinivasan, L Zhang, ...
arXiv preprint arXiv:1805.12298, 2018
Nonmonotonic aging and memory retention in disordered mechanical systems
Y Lahini, O Gottesman, A Amir, SM Rubinstein
Physical review letters 118 (8), 085501, 2017
Representation balancing mdps for off-policy policy evaluation
Y Liu, O Gottesman, A Raghu, M Komorowski, AA Faisal, F Doshi-Velez, ...
Advances in Neural Information Processing Systems 31, 2018
Improving sepsis treatment strategies by combining deep and kernel-based reinforcement learning
X Peng, Y Ding, D Wihl, O Gottesman, M Komorowski, HL Li-wei, A Ross, ...
AMIA Annual Symposium Proceedings 2018, 887, 2018
Multiple extinction routes in stochastic population models
O Gottesman, B Meerson
Physical Review E 85 (2), 021140, 2012
Behaviour policy estimation in off-policy policy evaluation: Calibration matters
A Raghu, O Gottesman, Y Liu, M Komorowski, A Faisal, F Doshi-Velez, ...
arXiv preprint arXiv:1807.01066, 2018
Interpretable off-policy evaluation in reinforcement learning by highlighting influential transitions
O Gottesman, J Futoma, Y Liu, S Parbhoo, L Celi, E Brunskill, ...
International Conference on Machine Learning, 3658-3667, 2020
A state variable for crumpled thin sheets
O Gottesman, J Andrejevic, CH Rycroft, SM Rubinstein
Communications Physics 1 (1), 1-7, 2018
Combining parametric and nonparametric models for off-policy evaluation
O Gottesman, Y Liu, S Sussex, E Brunskill, F Doshi-Velez
arXiv preprint arXiv:1905.05787, 2019
On the incompressibility of cylindrical origami patterns
F Bös, M Wardetzky, E Vouga, O Gottesman
Journal of Mechanical Design 139 (2), 2017
Furrows in the wake of propagating d-cones
O Gottesman, E Efrati, SM Rubinstein
Nature communications 6 (1), 1-7, 2015
Improving counterfactual reasoning with kernelised dynamic mixing models
S Parbhoo, O Gottesman, AS Ross, M Komorowski, A Faisal, I Bon, ...
PloS one 13 (11), e0205839, 2018
Learning to search efficiently for causally near-optimal treatments
S Håkansson, V Lindblom, O Gottesman, FD Johansson
Advances in Neural Information Processing Systems 33, 1333-1344, 2020
Learning Markov state abstractions for deep reinforcement learning
C Allen, N Parikh, O Gottesman, G Konidaris
Advances in Neural Information Processing Systems 34, 8229-8241, 2021
Weighted tensor decomposition for learning latent variables with partial data
O Gottesman, W Pan, F Doshi-Velez
International Conference on Artificial Intelligence and Statistics, 1664-1672, 2018
Optimistic Initialization for Exploration in Continuous Control
S Lobel, O Gottesman, C Allen, A Bagaria, G Konidaris
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7612-7619, 2022
Shaping Control Variates for Off-Policy Evaluation
S Parbhoo, O Gottesman, F Doshi-Velez
Offline Reinforcement Learning Workshop at Neural Information Processing …, 2020
Localized patterns in crushed conical shells
O Gottesman, E Vouga, SM Rubinstein, L Mahadevan
EPL (Europhysics Letters) 124 (1), 14005, 2018
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