Interpreting Deep Neural Networks Through Variable Importance. - Jonathan Ish-Horowicz; Dana Udwin; Seth R. Flaxman; Sarah Filippi; Lorin Crawford (CoRR, 2019)

Tropical Sufficient Statistics for Persistent Homology. - Anthea Monod; Sara Kalisnik; Juan Ángel Patino-Galindo; Lorin Crawford (SIAM J. Appl. Algebra Geom., 2019)

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes. - Wei Cheng; Gregory Darnell; Sohini Ramachandran; Lorin Crawford (CoRR, 2020)

A topological data analytic approach for discovering biophysical signatures in protein dynamics. - Wai-Shing Tang; Gabriel Monteiro da Silva; Henry Kirveslahti; Erin Skeens; Bibo Feng; Timothy Sudijono; Kevin K. Yang; Sayan Mukherjee 001; Brenda M. Rubenstein; Lorin Crawford (PLoS Comput. Biol., 2022)

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. - Hammaad Adam; Fan Yin; Huibin Hu; Neil A. Tenenholtz; Lorin Crawford; Lester Mackey; Allison Koenecke (NeurIPS, 2023)

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. - Hammaad Adam; Fan Yin; Mary Hu; Neil A. Tenenholtz; Lorin Crawford; Lester Mackey; Allison Koenecke (CoRR, 2023)

Deep self-supervised learning for biosynthetic gene cluster detection and product classification. - Carolina Rios-Martinez; Nicholas Bhattacharya; Ava P. Amini; Lorin Crawford; Kevin K. Yang (PLoS Comput. Biol., 2023)

BetaExplainer: A Probabilistic Method to Explain Graph Neural Networks. - Whitney Sloneker; Shalin Patel; Michael Wang; Lorin Crawford; Ritambhara Singh (CoRR, 2024)

A simple approach for local and global variable importance in nonlinear regression models. - Emily T. Winn-Nuñez; Maryclare Griffin; Lorin Crawford (Comput. Stat. Data Anal., 2024)

Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections. - Ke Li 028; Chrispin Chaguza; Julian Stamp; Yi Ting Chew; Nicholas F. G. Chen; David Ferguson; Sameer Pandya; Nick Kerantzas; Wade Schulz; Anne M. Hahn; C. Brandon Ogbunugafor; Virginia E. Pitzer; et al. (PLoS Comput. Biol., 2024)

Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks. - Helen Xie; Lorin Crawford; Ashley Mae Conard (BMC Bioinform., 2024)

ML-MAGES: A Machine Learning Framework for Multivariate Genetic Association Analyses with Genes and Effect Size Shrinkage. - Xiran Liu; Lorin Crawford; Sohini Ramachandran (RECOMB, 2025)