9 citations · 18 across the 5 of their papers we have counts for
6 papers
Clairvoyance: A Pipeline Toolkit for Medical Time Series
Daniel Jarrett, Jinsung Yoon, Ioana Bica +3
Time-series learning is the bread and butter of data-driven *clinical decision support*, and the recent explosion in ML research has demonstrated great potential in various healthc…
Model-Attentive Ensemble Learning for Sequence Modeling
Victor D. Bourgin, Ioana Bica, Mihaela van der Schaar
Medical time-series datasets have unique characteristics that make prediction tasks challenging. Most notably, patient trajectories often contain longitudinal variations in their i…
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge
Trent Kyono, Ioana Bica, Zhaozhi Qian +1
Selecting causal inference models for estimating individualized treatment effects (ITE) from observational data presents a unique challenge since the counterfactual outcomes are ne…
Learning Matching Representations for Individualized Organ Transplantation Allocation
Can Xu, Ahmed M. Alaa, Ioana Bica +3
Organ transplantation is often the last resort for treating end-stage illness, but the probability of a successful transplantation depends greatly on compatibility between donors a…
Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Daniel Jarrett, Alihan Hüyük +1
Building interpretable parameterizations of real-world decision-making on the basis of demonstrated behavior -- i.e. trajectories of observations and actions made by an expert maxi…
Strictly Batch Imitation Learning by Energy-based Distribution Matching
Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
Consider learning a policy purely on the basis of demonstrated behavior -- that is, with no access to reinforcement signals, no knowledge of transition dynamics, and no further int…