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

A Simple Baseline for Bayesian Uncertainty in Deep Learning. - Wesley J. Maddox; Pavel Izmailov; Timur Garipov; Dmitry P. Vetrov; Andrew Gordon Wilson (NeurIPS, 2019)

Subspace Inference for Bayesian Deep Learning. - Pavel Izmailov; Wesley J. Maddox; Polina Kirichenko; Timur Garipov; Dmitry P. Vetrov; Andrew Gordon Wilson (UAI, 2019)

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

Similarity of Neural Networks with Gradients. - Shuai Tang; Wesley J. Maddox; Charlie Dickens; Tom Diethe; Andreas C. Damianou (CoRR, 2020)

Fast Adaptation with Linearized Neural Networks. - Wesley J. Maddox; Shuai Tang; Pablo Garcia Moreno; Andrew Gordon Wilson; Andreas C. Damianou (AISTATS, 2021)

Kernel Interpolation for Scalable Online Gaussian Processes. - Samuel Stanton; Wesley J. Maddox; Ian A. Delbridge; Andrew Gordon Wilson (AISTATS, 2021)

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

Bayesian Optimization with High-Dimensional Outputs. - Wesley J. Maddox; Maximilian Balandat; Andrew Gordon Wilson; Eytan Bakshy (NeurIPS, 2021)

Conditioning Sparse Variational Gaussian Processes for Online Decision-making. - Wesley J. Maddox; Samuel Stanton; Andrew Gordon Wilson (NeurIPS, 2021)

Optimizing High-Dimensional Physics Simulations via Composite Bayesian Optimization. - Wesley J. Maddox; Qing Feng; Maximilian Balandat (CoRR, 2021)

When are Iterative Gaussian Processes Reliably Accurate? - Wesley J. Maddox; Sanyam Kapoor; Andrew Gordon Wilson (CoRR, 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)

Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders. - Samuel Stanton; Wesley J. Maddox; Nate Gruver; Phillip M. Maffettone; Emily Delaney; Peyton Greenside; Andrew Gordon Wilson (ICML, 2022)

On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. - Sanyam Kapoor; Wesley J. Maddox; Pavel Izmailov; Andrew Gordon Wilson (NeurIPS, 2022)

Low-precision arithmetic for fast Gaussian processes. - Wesley J. Maddox; Andres Potapczynski; Andrew Gordon Wilson (UAI, 2022)

Bayesian Optimization with Conformal Coverage Guarantees. - Samuel Stanton; Wesley J. Maddox; Andrew Gordon Wilson (CoRR, 2022)

Bayesian Optimization with Conformal Prediction Sets. - Samuel Stanton; Wesley J. Maddox; Andrew Gordon Wilson (AISTATS, 2023)

Materials Expert-Artificial Intelligence for Materials Discovery. - Yanjun Liu; Milena Jovanovic; Krishnanand Mallayya; Wesley J. Maddox; Andrew Gordon Wilson; Sebastian Klemenz; Leslie M. Schoop; Eun-Ah Kim (CoRR, 2023)