10 citations · 15 across the 4 of their papers we have counts for
4 papers
Scaling and Data Saturation in Protein Language Models
Aviv Spinner, Erika DeBenedictis, Corey M. Hudson
Data in biology is redundant, noisy, and sparse. How does the type and scale of available data impact model performance? In this work, we specifically investigate how protein langu…
Explicating feature contribution using Random Forest proximity distances
Leanne S. Whitmore, Anthe George, Corey M. Hudson
In Random Forests, proximity distances are a metric representation of data into decision space. By observing how changes in input map to the movement of instances in this space we…
Probability Series Expansion Classifier that is Interpretable by Design
Sapan Agarwal, Corey M. Hudson
This work presents a new classifier that is specifically designed to be fully interpretable. This technique determines the probability of a class outcome, based directly on probabi…
Mapping chemical performance on molecular structures using locally interpretable explanations
Leanne S. Whitmore, Anthe George, Corey M. Hudson
In this work, we present an application of Locally Interpretable Machine-Agnostic Explanations to 2-D chemical structures. Using this framework we are able to provide a structural…