Thakur S, Lorsung C, Yacoby Y, Doshi-Velez F, Pan W.
Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks. ICML Workshop on Uncertainty in Deep Learning. 2020;2 :1-18.
Paper Gottesman O, Futoma J, Liu Y, Parbhoo S, Celi LA, Brunskill E, Doshi-Velez F.
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. International Conference on Machine Learning (IMCL). 2020;2 :1-17.
Paper Yacoby Y, Pan W, Doshi-Velez F.
Failures of Variational Autoencoders and their Effects on Downstream Tasks. ICML Workshop on Uncertainty in Deep Learning. 2020;1 :1-39.
Paper M. Downs, J. Chu, Yacoby Y, Doshi-Velez F, WeiWei P.
CRUDS: Counterfactual Recourse Using Disentangled Subspaces. ICML Workshop on Human Interpretability in Machine Learning. 2020 :1-23.
Paper Guenais T, Vamvourellis D, Yacoby Y, Doshi-Velez F, Pan W.
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty. ICML Workshop on Uncertainty in Deep Learning. 2020;1 :1-24.
Paper J. Antoran, Yao J, Pan W, Doshi-Velez F, Hernandez-Lobato J.
Amortised Variational Inference for Hierarchical Mixture Models. ICML Workshop on Uncertainty in Deep Learning. 2020 :1-11.
Paper Yacoby Y, Pan W, Doshi-Velez F.
Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. Advances in Approximate Bayesian Inference. 2020;1 :1-17.
Paper Prasad N, Engelhardt B, Doshi-Velez F.
Defining Admissible Rewards for High-Confidence Policy Evaluation in Batch Reinforcement Learning. ACM Conference on Health, Inference and Learning. 2020;2 :1-9.
Paper McMahon A, Cooper W, Brown J, Carleton B, Doshi-Velez F, Kohane I, Goldman J, Hoffman M, Kamaleswaran R, Sakiyama M, et al. Big Data in the Assessment of Pediatric Medication Safety. Pediatrics. 2020;145 (2) :1-11.
Paper