High-Dimensional Gaussian Process Inference with Derivatives

15 February 2021

Papers citing "High-Dimensional Gaussian Process Inference with Derivatives"

11 / 11 papers shown

Title
Scaling Gaussian Process Regression with Full Derivative Observations Daniel Huang BDL GP 62 0 0 14 May 2025
Unexpected Improvements to Expected Improvement for Bayesian Optimization Sebastian Ament Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 92 82 0 08 Jan 2025
Linear cost and exponentially convergent approximation of Gaussian Matérn processes on intervals David Bolin Vaibhav Mehandiratta Alexandre B. Simas 56 1 0 16 Oct 2024
The Hyperdimensional Transform for Distributional Modelling, Regression and Classification Pieter Dewulf B. De Baets Michiel Stock 74 3 0 14 Nov 2023
Random Function Descent Felix Benning L. Döring 39 0 0 02 May 2023
Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes Yifan Chen H. Owhadi F. Schafer 96 31 0 03 Apr 2023
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 65 6 0 14 Oct 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 69 11 0 25 Aug 2022
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation Sebastian Ament Carla P. Gomes 62 9 0 16 Jun 2022
Scaling Gaussian Processes with Derivative Information Using Variational Inference Misha Padidar Xinran Zhu Leo Huang Jacob R. Gardner D. Bindel BDL 51 18 0 08 Jul 2021
Bayesian Numerical Methods for Nonlinear Partial Differential Equations Junyang Wang Jon Cockayne O. Chkrebtii T. Sullivan Chris J. Oates 111 19 0 22 Apr 2021