Sonali Parbhoo
Cited by
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Beyond sparsity: Tree regularization of deep models for interpretability
M Wu, MC Hughes, S Parbhoo, M Zazzi, V Roth, F Doshi-Velez
32nd AAAI Conference on Artificial Intelligence, 2017
Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART
N Bachmann, C Von Siebenthal, V Vongrad, T Turk, K Neumann, ...
Nature communications 10 (1), 3193, 2019
Combining kernel and model based learning for HIV therapy selection
S Parbhoo, J Bogojeska, M Zazzi, V Roth, F Doshi-Velez
AMIA Summits on Translational Science Proceedings 2017, 239, 2017
Real-time prediction of COVID-19 related mortality using electronic health records
P Schwab, A Mehrjou, S Parbhoo, LA Celi, J Hetzel, M Hofer, B Schölkopf, ...
Nature communications 12 (1), 1058, 2021
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
Regional tree regularization for interpretability in black box models
M Wu, S Parbhoo, M Hughes, R Kindle, L Celi, M Zazzi, V Roth, ...
arXiv preprint arXiv:1908.04494, 2019
Addressing leakage in concept bottleneck models
M Havasi, S Parbhoo, F Doshi-Velez
Advances in Neural Information Processing Systems 35, 23386-23397, 2022
Information bottleneck for estimating treatment effects with systematically missing covariates
S Parbhoo, M Wieser, A Wieczorek, V Roth
Entropy 22 (4), 389, 2020
Optimizing for interpretability in deep neural networks with tree regularization
M Wu, S Parbhoo, MC Hughes, V Roth, F Doshi-Velez
Journal of Artificial Intelligence Research 72, 1-37, 2021
Preferential mixture-of-experts: Interpretable models that rely on human expertise as much as possible
MF Pradier, J Zazo, S Parbhoo, RH Perlis, M Zazzi, F Doshi-Velez
AMIA Summits on Translational Science Proceedings 2021, 525, 2021
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty
S Joshi, S Parbhoo, F Doshi-Velez
arXiv preprint arXiv:2109.06312, 2021
Informed mcmc with bayesian neural networks for facial image analysis
A Kortylewski, M Wieser, A Morel-Forster, A Wieczorek, S Parbhoo, ...
arXiv preprint arXiv:1811.07969, 2018
A reinforcement learning design for HIV clinical trials
S Parbhoo
University of the Witwatersrand, Faculty of Science, School of Computer Science, 2014
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV
S Parbhoo, M Wieser, V Roth, F Doshi-Velez
Proceedings of Machine Learning Research 126, 1-19, 2020
Ncore: Neural counterfactual representation learning for combinations of treatments
S Parbhoo, S Bauer, P Schwab
arXiv preprint arXiv:2103.11175, 2021
Greedy structure learning of hierarchical compositional models
A Kortylewski, A Wieczorek, M Wieser, C Blumer, S Parbhoo, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
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
Bayesian markov blanket estimation
D Kaufmann, S Parbhoo, A Wieczorek, S Keller, D Adametz, V Roth
Artificial Intelligence and Statistics, 333-341, 2016
Risk sensitive dead-end identification in safety-critical offline reinforcement learning
TW Killian, S Parbhoo, M Ghassemi
arXiv preprint arXiv:2301.05664, 2023
Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment
CW Thorball, A Borghesi, N Bachmann, C Von Siebenthal, V Vongrad, ...
JAIDS Journal of Acquired Immune Deficiency Syndromes 85 (4), 517-524, 2020
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