1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
Seq-to-Final: A Benchmark for Tuning from Sequential Distributions to a Final Time Point
Christina X Ji, Ahmed M Alaa, David Sontag
Distribution shift over time occurs in many settings. Leveraging historical data is necessary to learn a model for the last time point when limited data is available in the final p…
Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning
Keying Kuang, Frances Dean, Jack B. Jedlicki +4
A digital twin is a virtual replica of a real-world physical phenomena that uses mathematical modeling to characterize and simulate its defining features. By constructing digital t…
Large-Scale Study of Temporal Shift in Health Insurance Claims
Christina X Ji, Ahmed M Alaa, David Sontag
Most machine learning models for predicting clinical outcomes are developed using historical data. Yet, even if these models are deployed in the near future, dataset shift over tim…
Conformalized Unconditional Quantile Regression
Ahmed M. Alaa, Zeshan Hussain, David Sontag
We develop a predictive inference procedure that combines conformal prediction (CP) with unconditional quantile regression (QR) -- a commonly used tool in econometrics that involve…