183 citations · 521 across the 26 of their papers we have counts for
7 papers · 1 filter
Conformal Sensitivity Analysis for Individual Treatment Effects
Mingzhang Yin, Claudia Shi, Yixin Wang +1
Estimating an individual treatment effect (ITE) is essential to personalized decision making. However, existing methods for estimating the ITE often rely on unconfoundedness, an as…
Adjusting for indirectly measured confounding using large-scale propensity scores
Linying Zhang, Yixin Wang, Martijn Schuemie +2
Confounding remains one of the major challenges to causal inference with observational data. This problem is paramount in medicine, where we would like to answer causal questions f…
Identifiable Deep Generative Models via Sparse Decoding
Gemma E. Moran, Dhanya Sridhar, Yixin Wang +1
We develop the sparse VAE for unsupervised representation learning on high-dimensional data. The sparse VAE learns a set of latent factors (representations) which summarize the ass…
Optimization-based Causal Estimation from Heterogenous Environments
Mingzhang Yin, Yixin Wang, David M. Blei
This paper presents a new optimization approach to causal estimation. Given data that contains covariates and an outcome, which covariates are causes of the outcome, and what is th…
Desiderata for Representation Learning: A Causal Perspective
Yixin Wang, Michael I. Jordan
Representation learning constructs low-dimensional representations to summarize essential features of high-dimensional data. This learning problem is often approached by describing…
Learning Equilibria in Matching Markets from Bandit Feedback
Meena Jagadeesan, Alexander Wei, Yixin Wang +2
Large-scale, two-sided matching platforms must find market outcomes that align with user preferences while simultaneously learning these preferences from data. Classical notions of…
Multi-Source Causal Inference Using Control Variates
Wenshuo Guo, Serena Wang, Peng Ding +2
While many areas of machine learning have benefited from the increasing availability of large and varied datasets, the benefit to causal inference has been limited given the strong…