Publications

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Here’s my google scholar

• Survival Mixture Density Networks. Machine Learning for Healthcare Conference. PMLR, 2022. Work by Xintian Han*, myself, and Rajesh Ranganath.

• Learning Invariant Representations with Missing Data (full version). CLeaR (Causal Learning and Reasoning) 2022. Work by myself*, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Puli, Rajesh Ranganath, and Andrew C. Miller. Work done as part of my internship at Apple Health AI.

• Learning Invariant Representations with Missing Data. NeurIPS 2021 DistShift Workshop. Work by myself*, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Puli, Rajesh Ranganath, and Andrew C. Miller. Work done as part of my internship at Apple Health AI.

• Inverse-Weighted Survival Games. NeurIPS 2021. Work by myself*, Xintian Han*, Aahlad Puli, Thomas Wies, Adler J. Perotte, and Rajesh Ranganath. A new way to estimate survival models by playing games involving both the failure and censoring distribution!

• Understanding Failures in Out-of-Distribution Detection with Deep Generative Models. ICML 2021. Work by Lily H. Zhang*, myself, and Rajesh Ranganath.

• Understanding Out-of-Distribution Detection with Deep Generative Models. ICLR 2021 RobustML workshop. Work by Lily H. Zhang*, myself, and Rajesh Ranganath.

• X-CAL: Explicit Calibration for Survival Analysis. NeurIPS 2020. Work by myself*, Xintian Han*, Aahlad Puli*, Adler J. Perotte, and Rajesh Ranganath.