Wesley J. Maddox

Cornell University — United States

Computer Science · Physical Sciences

9h-index437citations27works2.02yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(17), Advanced Multi-Objective Optimization Algorithms(5), Machine Learning and Data Classification(5), Neural Networks and Applications(4), Domain Adaptation and Few-Shot Learning(4)

Publications27 total

Materials Expert-Artificial Intelligence for materials discovery
Communications Materials·2025· 2 citedOpen Access
Materials Expert-Artificial Intelligence for Materials Discovery
arXiv (Cornell University)·2023· 1 citedOpen Access
Bayesian Optimization with Conformal Prediction Sets
arXiv (Cornell University)·2022· 1 citedOpen Access
Low-Precision Arithmetic for Fast Gaussian Processes
arXiv (Cornell University)·2022Open Access
Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
arXiv (Cornell University)·2022· 1 citedOpen Access
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
arXiv (Cornell University)·2022· 9 citedOpen Access
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
arXiv (Cornell University)·2022· 22 citedOpen Access
When are Iterative Gaussian Processes Reliably Accurate?
arXiv (Cornell University)·2021· 1 citedOpen Access
Optimizing High-Dimensional Physics Simulations via Composite Bayesian\n Optimization
arXiv (Cornell University)·2021· 2 citedOpen Access
Optimizing High-Dimensional Physics Simulations via Composite Bayesian Optimization
arXiv (Cornell University)·2021Open Access
Conditioning Sparse Variational Gaussian Processes for Online\n Decision-making
arXiv (Cornell University)·2021· 5 citedOpen Access
Conditioning Sparse Variational Gaussian Processes for Online Decision-making
arXiv (Cornell University)·2021· 2 citedOpen Access
Bayesian Optimization with High-Dimensional Outputs
arXiv (Cornell University)·2021· 9 citedOpen Access
Rethinking Parameter Counting: Effective Dimensionality Revisited
2021
Fast Adaptation with Linearized Neural Networks
arXiv (Cornell University)·2021· 1 citedOpen Access
Kernel Interpolation for Scalable Online Gaussian Processes
arXiv (Cornell University)·2021· 4 citedOpen Access
Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
arXiv (Cornell University)·2021· 5 citedOpen Access
Similarity of Neural Networks with Gradients
arXiv (Cornell University)·2020· 12 citedOpen Access
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited
arXiv (Cornell University)·2020· 28 citedOpen Access
Function-Space Distributions over Kernels
arXiv (Cornell University)·2019· 8 citedOpen Access
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Frequent Co-authors

Andrew Gordon Wilson(19), Pavel Izmailov(4), Gregory W. Benton(4), Timur Garipov(3), Dmitry Vetrov(3), Samuel C. Stanton(3), Polina Kirichenko(2), Shuai Tang(2), Andreas Damianou(2), Sanyam Kapoor(2), Maximilian Balandat(2), Samuel Stanton(2), Y. Liu(2), Milena Jovanović(2), Krishnanand Mallayya(2), Sebastian Klemenz(2), Leslie M. Schoop(2), Eun-Ah Kim(2), Andrew Gordon Wilson(1), Sneha Grandhi(1)