Year	Publication
2022	T. Killian, M. Ghassemi, S. Joshi Counterfactually Guided Policy Transfer in Clinical Settings. Conference on Health, Inference, and Learning (PMLR, to Appear).
2022	S. Joshi*, S. Parbhoo*, F. Doshi-Velez Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. Preprint 2022.
2022	M. Pawelczyk, C. Agarwal, S. Joshi, S. Upadhyay, H. Lakkaraju Exploring Counterfactual Explanations through the lens of Adversarial Examples: A Theoretical and Empirical Analysis. AISTATS 2022.
2021	S. Joshi*, S. Parbhoo*, F. Doshi-Velez Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. IMLH@ICML, Preprint 2021.
2021	S. Upadhyay*, S. Joshi*, H. Lakkaraju Towards Robust and Reliable Algorithmic Recourse. NeurIPS 2021.
2021	H. Singh, S Joshi, F. Doshi-Velez, H. Lakkaraju Learning Under Adversarial and Interventional Shifts. Preprint 2021.
2021	S. Gowda, S. Joshi, H. Zhang, M. Ghassemi Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. ACM CIKM, 2021.
2020	H. Zhang, N. Dullerud, L. Seyyed-Kalantari, Q. Morris, S. Joshi, M. Ghassemi An empirical framework for domain generalization in clinical settings. ACM CHIL, 2021.
2020	V. Cheng, V. M. Suriyakumar, N. Dullerud, S. Joshi, M. Ghassemi Can You Fake It Until You Make It? Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. ACM FAccT, 2021.
2020	M. D. McCradden, S. Joshi, J. A. Anderson, M. Mazwi, A. Goldenberg, R. Z. Shaul Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. JAMIA, 2020.
2020	S. Wang*, S. Yi*, S. Joshi, M. Ghassemi Confounding Feature Acquisition for Causal Effect Estimation. ML4H@NeurIPS 2020 Proceedings (to appear).
2020	I. Chen*, S. Joshi*, M. Ghassemi, R. Ranganath Probabilistic Machine Learning for Healthcare. Annual Review of Biomedical Data Science 2020.
2020	I. Chen, E. Pierson, S. Rose, S. Joshi, M. Ghassemi Ethical Machine Learning in Health Care. Annual Review of Biomedical Data Science 2020.
2020	F. Rudzicz, S. Joshi Explainable AI for the Operating Theater. Springer 2020.
2020	S. Tonekaboni*, S. Joshi*, K. Campbell, D. Duvenaud, A. Goldenberg What went wrong and when? Instance-wise Feature Importance for Time-series Models. NeurIPS 2020.
2020	A. Yeung, S. Joshi, J. Williams, F. Rudzicz Sequential Explanations with Mental Model-Based Policies. Workshop on Human Interpretability in Machine Learning @ICML 2020 (Spotlight).
2020	M. McCradden, S. Joshi, J. Anderson, M. Mazwi, A. Goldenberg, R. Shaul Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. JAMIA 2020.
2020	M. McCradden, S. Joshi, M. Mazwi, J. Anderson Ethical limitations of algorithmic fairness solutions in health care machine learning. LDH 2020, AIES 2020, FairML for Health @NeurIPS 2020.
2020	I. Chen, S. Joshi, M. Ghassemi Treating health disparities with artificial intelligence. Nature Medicine 2020.
2019	S. Tonekaboni, S. Joshi, A. Goldenberg Individualized Feature Importance for Time Series Risk Prediction Models. NeurIPS ML4H Workshop 2019.
2019	S. Yi, S. Wang, S. Joshi, M. Ghassemi Fair and Robust Treatment Effect Estimates: Estimation Under Treatment and Outcome Disparity with Deep Neural Models. NeurIPS ML4H and Fair ML for Health Workshop 2019.
2019	M. McCradden, S. Tonekaboni, S. Joshi, A. Goldenberg Five Pillars of Explainable Clinical Machine Learning. Stanford Frontier of AI-Assisted Care (FAC) Scientific Symposium.
2019	S. Tonekaboni, S. Joshi, M. McCradden, A. Goldenberg What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC 2019.
2019	S. Joshi, O. Koyejo, W. Vijitbenjaronk, B. Kim, J. Ghosh Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. SafeML Workshop @ICLR 2019.
2018	S. Joshi, R. Khanna, J. Ghosh Co-regularized Monotone Retargeting for Semi-supervised LeTOR. SDM 2018.
2018	S. Joshi, S. Gunasekar, D. Sontag J. Ghosh Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. MLHC 2018.
2016	S. Joshi, O. Koyejo, M. Reid, J. Ghosh Rényi divergence minimization based co-regularized multiview clustering. ECML-PKDD Journal track 2016.
2016	S. Joshi, O. Koyejo, J. Ghosh Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. ICHI 2016.
2014	S. Joshi, O. Koyejo, J. Ghosh Multiview Clustering via Constrained Bayesian Inference. Workshop on Divergence Methods for Probabilistic Inference @ICML 2014.