1 citations · 2 across the 7 of their papers we have counts for
7 papers
Towards causal effect estimation with learned instrument representations
Frances Dean, Jenna Fields, Radhika Bhalerao +2
Instrumental variable (IV) methods mitigate bias from unobserved confounding in observational causal inference but rely on the availability of a valid instrument, which can often b…
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…
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis +1
Causal inferences from a randomized controlled trial (RCT) may not pertain to a target population where some effect modifiers have a different distribution. Prior work studies gene…
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…
Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs
Ayush Jain, Marie Laure-Charpignon, Irene Y. Chen +2
The drug development pipeline for a new compound can last 10-20 years and cost over 10 billion. Drug repurposing offers a more time- and cost-effective alternative. Computational a…
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…