Ghosh S, Yao J, Doshi-Velez F.
Model Selection in Bayesian Neural Networks via Horseshoe Priors. Journal of Machine Learning Research. 2019;20 (182) :1-46.
Paper Prasad N, Engelhardt B, Doshi-Velez F.
Defining Admissible Rewards for High Confidence Policy Evaluation. NeurIPS Workshop on Safety and Robustness in Decision-Making, . 2019;1 :1-12.
Paper Ross A, Du J, Sharvit Y, Doshi-Velez F.
Controlled Direct Effect Priors for Bayesian Neural Networks. NeurIPS Workshop on Bayesian Deep Learning. 2019;1 :1-8.
Paper Jacobs M, Perlis R, Pradier M, Doshi-Velez F, Mynatt E, Gajos K.
Integrating AI Recommendations into The Pharmacologic Management of Major Depressive Disorder. CSCW Workshop: Identifying Challenges and Opportunities in Human–AI Collaboration in Healthcare. 2019;1 :1-5.
Paper Ren J, Russell R, Doshi-Velez F.
Prediction Focused Topic Models Via Vocab Filtering. NeurIPS Workshop on Human-Centric ML. 2019;1 :1-12.
Paper Pradier M, Pan W, Yao J, Ghosh S, Doshi-Velez F.
Projected BNNs: Avoiding Weight-space Pathologies by Learning Latent Representations of Neural Network Weights. ACML Workshop on Weakly Supervised Learning Workshop. 2019;3 :1-15.
Paper Ren J, Kunes R, Doshi-Velez F.
Prediction Focused Topic Models for Electronic Health Records. NeurIPS Workshop on Machine Learning for Health. 2019;1 :1-13.
Paper Wiens J, Saria S, Sendak M, Ghassemi M, Liu V, Doshi-Velez F, Jung K, Heller K, Kale D, Saeed M, et al. Do no harm: A roadmap for responsible machine learning for healthcare. Nature Medicine. 2019;25 (10) :1337-1340.
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Amendments Amir O, Doshi-Velez F, Sarne D.
Summarizing Agent Strategies. Journal of Autonomous Agents and Multi-Agent Systems (AAMAS). 2019;33 :628-644.
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