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Contrastive Corpus Attribution for Explaining Representations
Chris Lin, Hugh Chen, Chanwoo Kim +1
Despite the widespread use of unsupervised models, very few methods are designed to explain them. Most explanation methods explain a scalar model output. However, unsupervised mode…
Algorithms to estimate Shapley value feature attributions
Hugh Chen, Ian C. Covert, Scott M. Lundberg +1
Feature attributions based on the Shapley value are popular for explaining machine learning models; however, their estimation is complex from both a theoretical and computational s…
Learning to Estimate Shapley Values with Vision Transformers
Ian Covert, Chanwoo Kim, Su-In Lee
Transformers have become a default architecture in computer vision, but understanding what drives their predictions remains a challenging problem. Current explanation approaches re…
Moment Matching Deep Contrastive Latent Variable Models
Ethan Weinberger, Nicasia Beebe-Wang, Su-In Lee
In the contrastive analysis (CA) setting, machine learning practitioners are specifically interested in discovering patterns that are enriched in a target dataset as compared to a…