10 citations · 26 across the 6 of their papers we have counts for
6 papers
Estimating the causal effects of multiple intermittent treatments with application to COVID-19
Liangyuan Hu, Jiayi Ji, Himanshu Joshi +2
To draw real-world evidence about the comparative effectiveness of multiple time-varying treatments on patient survival, we develop a joint marginal structural survival model and a…
Hölder Bounds for Sensitivity Analysis in Causal Reasoning
Serge Assaad, Shuxi Zeng, Henry Pfister +2
We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U. Using Hölder's inequality, we derive a set of bound…
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE
Junya Chen, Zhe Gan, Xuan Li +10
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years. However, these contrastive schemes are notoriously resource de…
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization
Qing Guo, Junya Chen, Dong Wang +6
Successful applications of InfoNCE and its variants have popularized the use of contrastive variational mutual information (MI) estimators in machine learning. While featuring supe…
Double Robust Representation Learning for Counterfactual Prediction
Shuxi Zeng, Serge Assaad, Chenyang Tao +3
Causal inference, or counterfactual prediction, is central to decision making in healthcare, policy and social sciences. To de-bias causal estimators with high-dimensional data in…
Counterfactual Representation Learning with Balancing Weights
Serge Assaad, Shuxi Zeng, Chenyang Tao +5
A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation lea…