Function-Space Distributions over Kernels. - Gregory W. Benton; Wesley J. Maddox; Jayson P. Salkey; Julio Albinati; Andrew Gordon Wilson (NeurIPS, 2019)

Learning Invariances in Neural Networks from Training Data. - Gregory W. Benton; Marc Finzi; Pavel Izmailov; Andrew Gordon Wilson (NeurIPS, 2020)

Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited. - Wesley J. Maddox; Gregory W. Benton; Andrew Gordon Wilson (CoRR, 2020)

Trajectory Based Podcast Recommendation. - Greg Benton; Ghazal Fazelnia; Alice Wang; Ben Carterette (CoRR, 2020)

Learning Invariances in Neural Networks. - Gregory W. Benton; Marc Finzi; Pavel Izmailov; Andrew Gordon Wilson (CoRR, 2020)

Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling. - Gregory W. Benton; Wesley J. Maddox; Sanae Lotfi; Andrew Gordon Wilson (ICML, 2021)

Residual Pathway Priors for Soft Equivariance Constraints. - Marc Finzi; Greg Benton; Andrew Gordon Wilson (NeurIPS, 2021)

Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes. - Gregory W. Benton; Wesley J. Maddox; Andrew Gordon Wilson (ICML, 2022)

Bayesian Model Selection, the Marginal Likelihood, and Generalization. - Sanae Lotfi; Pavel Izmailov; Gregory W. Benton; Micah Goldblum; Andrew Gordon Wilson (ICML, 2022)

Function Space Reasoning in Gaussian Processes and Neural Networks - Greg Benton (2023)

Building Process Mining Dashboards Manually or AI-assisted with Celonis Views. - Carolin Ullrich; Teodora Lata; Greg Benton (ICPM Doctoral Consortium / Demo, 2024)