22 citations · 46 across the 7 of their papers we have counts for
7 papers
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks
Jeremy Goldwasser, Giles Hooker
Counterfactuals are a popular framework for interpreting machine learning predictions. These what if explanations are notoriously challenging to create for computer vision models:…
Gaussian Rank Verification
Jeremy Goldwasser, Will Fithian, Giles Hooker
Statistical experiments often seek to identify random variables with the largest population means. This inferential task, known as rank verification, has been well-studied on Gauss…
Statistical Significance of Feature Importance Rankings
Jeremy Goldwasser, Giles Hooker
Feature importance scores are ubiquitous tools for understanding the predictions of machine learning models. However, many popular attribution methods suffer from high instability…
Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation
Rui Yang, Qingcheng Zeng, Keen You +13
This study introduces Ascle, a pioneering natural language processing (NLP) toolkit designed for medical text generation. Ascle is tailored for biomedical researchers and healthcar…
Stabilizing Estimates of Shapley Values with Control Variates
Jeremy Goldwasser, Giles Hooker
Shapley values are among the most popular tools for explaining predictions of blackbox machine learning models. However, their high computational cost motivates the use of sampling…
Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review
Irene Li, Jessica Pan, Jeremy Goldwasser +10
Electronic health records (EHRs), digital collections of patient healthcare events and observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and…
Forest Fire Clustering for Single-cell Sequencing with Iterative Label Propagation and Parallelized Monte Carlo Simulation
Zhanlin Chen, Jeremy Goldwasser, Philip Tuckman +3
In the era of single-cell sequencing, there is a growing need to extract insights from data with clustering methods. Here, we introduce Forest Fire Clustering, an efficient and int…