1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Using Shapley interactions to understand how models use structure
Divyansh Singhvi, Diganta Misra, Andrej Erkelens +3
Language is an intricately structured system, and a key goal of NLP interpretability is to provide methodological insights for understanding how language models represent this stru…
cs.LG2022★ 1 cited
Interpreting County Level COVID-19 Infection and Feature Sensitivity using Deep Learning Time Series Models
Md Khairul Islam, Di Zhu, Yingzheng Liu +3
Interpretable machine learning plays a key role in healthcare because it is challenging in understanding feature importance in deep learning model predictions. We propose a novel f…