20 citations · 47 across the 6 of their papers we have counts for
6 papers
A Unified f-divergence Framework Generalizing VAE and GAN
Jaime Roquero Gimenez, James Zou
Developing deep generative models that flexibly incorporate diverse measures of probability distance is an important area of research. Here we develop an unified mathematical frame…
Causal aggregation: estimation and inference of causal effects by constraint-based data fusion
Jaime Roquero Gimenez, Dominik Rothenhäusler
In causal inference, it is common to estimate the causal effect of a single treatment variable on an outcome. However, practitioners may also be interested in the effect of simulta…
Identifying Invariant Factors Across Multiple Environments with KL Regression
Jaime Roquero Gimenez, James Zou
Many datasets are collected from multiple environments (e.g. different labs, perturbations, etc.), and it is often advantageous to learn models and relations that are invariant acr…
Discovering Conditionally Salient Features with Statistical Guarantees
Jaime Roquero Gimenez, James Zou
The goal of feature selection is to identify important features that are relevant to explain an outcome variable. Most of the work in this domain has focused on identifying globall…
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization
Jaime Roquero Gimenez, James Zou
The Model-X knockoff procedure has recently emerged as a powerful approach for feature selection with statistical guarantees. The advantage of knockoff is that if we have a good mo…
Knockoffs for the mass: new feature importance statistics with false discovery guarantees
Jaime Roquero Gimenez, Amirata Ghorbani, James Zou
An important problem in machine learning and statistics is to identify features that causally affect the outcome. This is often impossible to do from purely observational data, and…