Publications

2019
Gottesman O, Johansson F, Komorowski M, Faisal A, Sontag D, Doshi-Velez F, Celi L. Guidelines for reinforcement learning in healthcare. Nature Medicine. 2019;25 :16-18. Paper
2018
Lage I, Chen E, He J, Narayanan M, Gershman S, Kim B, Doshi-Velez F. An Evaluation of the Human-Interpretability of Explanation. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Correcting and Critiquing Trends in Machine Learning. 2018. Paper
Pradier MF, Pan W, Yao J, Ghosh S, Doshi-Velez F. Projected BNNs: Avoiding weight-space pathologies by projecting neural network weights. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Bayesian Deep Learning . 2018. Paper
Fernandez-Pradier M, Pan W, Yao M, Singh R, Doshi-Velez F. Hierarchical Stick-breaking Feature Paintbox. Conference on Neural Information Processing Systems (NeurIPS) Workshop on All of Bayesian Nonparametrics. 2018. Paper
Futoma J, Hughes MC, Doshi-Velez F. Prediction-Constrained POMDPs. Conference on Neural Information Processing Systems (NeurIPS) Workshop on Reinforcement Learning under Partial Observability . 2018. Paper
Parbhoo S, Gottesman O, Ross AS, Komorowski M, Faisal A, Bon I, Roth V, Doshi-Velez F. Improving counterfactual reasoning with kernelised dynamic mixing models. PLoS ONE . 2018;13 (11). Paper
Lage I, Ross A, Kim B, Gershman S, Doshi-Velez F. Human-in-the-Loop Interpretability Prior. Conference on Neural Information Processing Systems (NeurIPS). 2018. Paper
Wu M, Hughes M, Parbhoo S, Zazzi M, Roth V, Doshi-Velez F. Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. Association for the Advancement of Artificial Intelligence (AAAI). 2018. Paper
Masood MA, Doshi-Velez F. Diversity-Inducing Policy Gradient: Using MMD to find a set of policies that are diverse in terms of stete-visitation. International Conference on Machine Learning (ICML) Exploration in Reinforcement Learning Workshop. 2018. Paper
Peng X, Ding Y, Wihl D, Gottesman O, Komorowski M, Lehman L-wei H, Ross A, Faisal A, Doshi-Velez F. Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. American Medical Informatics Association (AMIA) Annual Symposium. 2018. Paper
Ghosh S, Yao J, Doshi-Velez F. Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors, in Proceedings of the 35th International Conference on Machine Learning (ICML). Vol 80. Stockholm, Sweden ; 2018. Paper
Depeweg S, Hernandez-Lobato JM, Doshi-Velez F, Udluft S. Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning, in Proceedings of the 35th International Conference on Machine Learning (ICML). Vol 80. Stockholm, Sweden ; 2018. Paper
Gottesman O, Pan W, Doshi-Velez F. Weighted Tensor Decomposition for Learning Latent Variables with Partial Data, in Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018. Vol 84. Lanzarote, Spain ; 2018. Paper
Hughes MC, Hope G, Weiner L, Thomas H. McCoy J, Perlis RH, Sudderth E, Doshi-Velez F. Semi-Supervised Prediction-Constrained Topic Models, in Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018. Vol 84. Lanzarote, Spain ; 2018. Paper
Amir O, Doshi-Velez F, Sarne D. Agent Strategy Summarization. Autonomous Agents and Multiagent Systems, Blue Sky Ideas Track. 2018. Paper
Doshi-Velez F, Kortz M, Budish R, Bavitz C, Gershman S, O'Brien D, Shieber S, Waldo J, Weinberger D, Wood A. Accountability of AI Under the Law: The Role of Explanation. Privacy Law Scholars Conference. 2018. Paper
Jin L, Doshi-Velez F, Miller T, Schuler W, Schwartz L. Unsupervised Grammar Induction with Depth-bounded PCFG. Association for Computational Linguistics. 2018. Paper
Ross AS, Doshi-Velez F. Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients. Association for the Advancement of Artificial Intelligence (AAAI). 2018. Paper
Yao J, Killian T, Konidaris G, Doshi-Velez F. Direct Policy Transfer via Hidden Parameter Markov Decision Processes. International Conference on Machine Learning (ICML) Workshop on Lifelong Learning,. 2018. Paper
Raghu A, Gottesman O, Liu Y, Komorowski M, Faisal A, Doshi-Velez F, Brunskill E. Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. International Conference on Machine Learning (ICML) Workshop on CausalML. 2018. Paper

Pages