Spotlight Oral at ICML 2020 Workshop on Human Interpretability in Machine Learning (WHI)

“Scalable learning of interpretable rules for the dynamic microbiome domain” from Venkata Suhas Maringanti,  Vanni Bucci,  Georg K. Gerber.

A new fully-differentiable model that learns human-interpretable rules operating on microbiome time-series data to classify host status .Our approach uses a novel 5-layer Neural Inductive Logic Programming (ILP)-type model with domain-specific microbiome and temporal attention mechanisms that outputs human-interpretable classification rules.