Publications and preprints


My Google Scholar page is here.


FastSHAP: Real-Time Shapley Value Estimation [code] [video]
Neil Jethani*, Mukund Sudarshan*, Ian Covert*, Su-In Lee, Rajesh Ranganath
Under review

Explaining by Removing: A Unified Framework for Model Explanation [code] [video]
Ian Covert, Scott Lundberg, Su-In Lee
In the Journal of Machine Learning Research (JMLR 2021)

Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression [code] [blog]
Ian Covert, Su-In Lee
In the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021)

Understanding Global Feature Contributions With Additive Importance Measures [code] [short video] [blog]
Ian Covert, Scott Lundberg, Su-In Lee
In the 34th Conference on Neural Information Processing Systems (NeurIPS 2020)

Neural Granger Causality [code]
Alex Tank*, Ian Covert*, Nicholas Foti, Ali Shojaie, Emily Fox
In Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2021)

Deep Unsupervised Feature Selection [code]
Ian Covert, Uygar Sümbül, Su-In Lee
Preprint

Temporal Graph Convolutional Networks for Automatic Seizure Detection
Ian Covert, Balu Krishnan, Imad Njam, Jiening Zhan, Matthew Shore, John Hixson, Ming Jack Po
In the 3rd Conference on Machine Learning for Healthcare (MLHC 2019)

Workshop papers

Disrupting Model Training With Adversarial Shortcuts
Ivan Evtimov, Ian Covert, Aditya Kusupati, Tadayoshi Kohno
In the Adversarial ML Workshop at ICML 2021

Feature Removal Is a Unifying Principle for Model Explanation Methods
Ian Covert, Scott Lundberg, Su-In Lee
In the Machine Learning Retrospectives & Meta-Analyses (ML-RSA) Workshop at NeurIPS 2020

Shapley Feature Utility
Ian Covert, Scott Lundberg, Su-In Lee
In Machine Learning for Computational Biology (MLCB 2019)

Principal Genes Selection
Ian Covert, Uygar Sümbül, Su-In Lee
In Machine Learning for Computational Biology (MLCB 2019)

EEG Seizure Detection via Deep Neural Networks: Application and Interpretation
Jiening Zhan, Hector Yee, Ian Covert, Jiang Wu, Albee Ling, Matthew Shore, Eric Teasley, Rebecca Davies, Tiffany Kung, Justin Tansuwan, John Hixson and Ming Jack Po
In the Machine Learning for Healthcare (ML4H) Workshop at NeurIPS 2019

An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery
Alex Tank, Ian Covert, Nicholas Foti, Ali Shojaie, Emily Fox
In the Time Series Workshop (TSW) at NeurIPS 2017