Additive Gaussian Processes Revisited

20 June 2022

Papers citing "Additive Gaussian Processes Revisited"

13 / 13 papers shown

Title
Challenges in interpretability of additive models Xinyu Zhang Julien Martinelli S. T. John AAML AI4CE 115 1 0 14 Apr 2025
High Dimensional Bayesian Optimization using Lasso Variable Selection Vu Viet Hoang Hung The Tran Sunil R. Gupta Vu Nguyen 179 0 0 02 Apr 2025
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 118 0 0 28 Mar 2024
Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression Lu Zou Liang Ding 78 0 0 20 Mar 2024
Combining additivity and active subspaces for high-dimensional Gaussian process modeling M. Binois Victor Picheny 85 0 0 06 Feb 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression Kevin Li Max Balakirsky Simon Mak 70 3 0 23 Oct 2023
Graph-Structured Kernel Design for Power Flow Learning using Gaussian Processes Parikshit Pareek Deepjyoti Deka Sidhant Misra 47 1 0 15 Aug 2023
Beyond Intuition, a Framework for Applying GPs to Real-World Data K. Tazi J. Lin Ross Viljoen A. Gardner S. T. John Hong Ge Richard Turner GP 55 4 0 06 Jul 2023
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization Anthony Bardou Patrick Thiran Thomas Begin 58 6 0 31 May 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 105 6 0 26 May 2023
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery T. Tang Simon Mak David B. Dunson 55 4 0 01 Feb 2023
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? Juliusz Ziomek Haitham Bou-Ammar 109 24 0 30 Jan 2023
Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes Kyle Hayes Michael W. Fouts Ali Baheri D. Mebane 77 0 0 26 May 2022