PhD Candidate, Computer Science, NYU
email: goldstein [at] nyu [dot] edu
pronouns: he/him/his
Here’s my google scholar
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.