The age of secrecy and unfairness in recidivism prediction. - Cynthia Rudin; Caroline Wang; Beau Coker (CoRR, 2018)

Learning a Generative Model of Cancer Metastasis. - Benjamin Kompa; Beau Coker (CoRR, 2019)

Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks. - Beau Coker; Melanie F. Pradier; Finale Doshi-Velez (CoRR, 2019)

Learning a Latent Space of Highly Multidimensional Cancer Data. - Benjamin Kompa; Beau Coker (PSB, 2020)

PoRB-Nets: Poisson Process Radial Basis Function Networks. - Beau Coker; Melanie Fernandes Pradier; Finale Doshi-Velez (UAI, 2020)

Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data. - Beau Coker; Weiwei Pan; Finale Doshi-Velez (CoRR, 2021)

A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results. - Beau Coker; Cynthia Rudin; Gary King (Manag. Sci., 2021)

Wide Mean-Field Bayesian Neural Networks Ignore the Data. - Beau Coker; Wessel P. Bruinsma; David R. Burt; Weiwei Pan; Finale Doshi-Velez (AISTATS, 2022)

Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees. - Wenying Deng; Beau Coker; Rajarshi Mukherjee; Jeremiah Z. Liu; Brent A. Coull (NeurIPS, 2022)

Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees. - Wenying Deng; Beau Coker; Jeremiah Zhe Liu; Brent A. Coull (CoRR, 2022)

An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks. - Jiayu Yao; Yaniv Yacoby; Beau Coker; Weiwei Pan; Finale Doshi-Velez (CoRR, 2022)

Variational Deep Learning via Implicit Regularization. - Jonathan Wenger; Beau Coker; Juraj Marusic; John P. Cunningham (CoRR, 2025)