602 citations · 2.9k across the 103 of their papers we have counts for
13 papers · 1 filter
Adapting to Latent Subgroup Shifts via Concepts and Proxies
Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour +7
We address the problem of unsupervised domain adaptation when the source domain differs from the target domain because of a shift in the distribution of a latent subgroup. When thi…
Efficient Conditionally Invariant Representation Learning
Roman Pogodin, Namrata Deka, Yazhe Li +3
We introduce the Conditional Independence Regression CovariancE (CIRCE), a measure of conditional independence for multivariate continuous-valued variables. CIRCE applies as a regu…
Controlling Moments with Kernel Stein Discrepancies
Heishiro Kanagawa, Alessandro Barp, Arthur Gretton +1
Kernel Stein discrepancies (KSDs) measure the quality of a distributional approximation and can be computed even when the target density has an intractable normalizing constant. No…
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment
Liyuan Xu, Arthur Gretton
We consider the estimation of average and counterfactual treatment effects, under two settings: back-door adjustment and front-door adjustment. The goal in both cases is to recover…
Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference
Pierre Glaser, Michael Arbel, Samo Hromadka +2
We introduce two synthetic likelihood methods for Simulation-Based Inference (SBI), to conduct either amortized or targeted inference from experimental observations when a high-fid…
A kernel Stein test of goodness of fit for sequential models
Jerome Baum, Heishiro Kanagawa, Arthur Gretton
We propose a goodness-of-fit measure for probability densities modeling observations with varying dimensionality, such as text documents of differing lengths or variable-length seq…