Additive Gaussian Processes

19 December 2011

Papers citing "Additive Gaussian Processes"

30 / 30 papers shown

Title
Challenges in interpretability of additive models Xinyu Zhang Julien Martinelli S. T. John AAML AI4CE 32 1 0 14 Apr 2025
Preconditioned Additive Gaussian Processes with Fourier Acceleration Theresa Wagner Tianshi Xu Franziska Nestler Yuanzhe Xi Martin Stoll 51 1 0 01 Apr 2025
Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory Sergei Manzhos Johann Luder Manabu Ihara Manabu Ihara 39 0 0 08 Feb 2025
Dynamic Online Ensembles of Basis Expansions Daniel Waxman Petar M. Djurić 43 3 0 02 May 2024
Explainable Learning with Gaussian Processes Kurt Butler Guanchao Feng P. Djuric 39 1 0 11 Mar 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 32 17 0 03 Feb 2024
A Bayesian Take on Gaussian Process Networks Enrico Giudice Jack Kuipers G. Moffa GP 29 3 0 20 Jun 2023
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks Mohamed Aziz Bhouri M. Joly Robert Yu S. Sarkar P. Perdikaris BDL UQCV AI4CE 19 1 0 14 Feb 2023
Orders-of-coupling representation with a single neural network with optimal neuron activation functions and without nonlinear parameter optimization Sergei Manzhos Manabu Ihara 18 8 0 11 Feb 2023
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery T. Tang Simon Mak David B. Dunson 22 4 0 01 Feb 2023
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 38 199 0 07 Jun 2022
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 33 0 0 26 May 2022
High-dimensional additive Gaussian processes under monotonicity constraints A. F. López-Lopera F. Bachoc O. Roustant 31 9 0 17 May 2022
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis Kirill Antonov E. Raponi Hao Wang Carola Doerr 25 10 0 28 Apr 2022
Online structural kernel selection for mobile health Eura Shin Pedja Klasnja S. Murphy Finale Doshi-Velez 15 1 0 21 Jul 2021
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes Will Tebbutt Arno Solin Richard Turner 21 8 0 18 Jun 2021
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui 33 30 0 18 Mar 2021
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization Xingchen Ma Matthew B. Blaschko 21 7 0 21 Jun 2020
Randomly Projected Additive Gaussian Processes for Regression Ian A. Delbridge D. Bindel A. Wilson 21 27 0 30 Dec 2019
Graph Convolutional Gaussian Processes Ian Walker Ben Glocker GNN 17 35 0 14 May 2019
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly Kirthevasan Kandasamy Karun Raju Vysyaraju W. Neiswanger Biswajit Paria Christopher R. Collins J. Schneider Barnabás Póczós Eric P. Xing 29 174 0 15 Mar 2019
Differentiable Compositional Kernel Learning for Gaussian Processes Shengyang Sun Guodong Zhang Chaoqi Wang Wenyuan Zeng Jiaman Li Roger C. Grosse BDL 13 69 0 12 Jun 2018
Posterior Inference for Sparse Hierarchical Non-stationary Models K. Monterrubio-Gómez L. Roininen S. Wade Theo Damoulas Mark Girolami 27 27 0 04 Apr 2018
Decentralized High-Dimensional Bayesian Optimization with Factor Graphs T. Hoang Q. Hoang Ruofei Ouyang K. H. Low 23 53 0 19 Nov 2017
Gaussian Processes for Survival Analysis T. Fernandez Nicolás Rivera Yee Whye Teh GP 22 75 0 02 Nov 2016
The Multivariate Generalised von Mises distribution: Inference and applications Alexandre Khae Wu Navarro J. Frellsen Richard Turner 17 24 0 16 Feb 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA Kirthevasan Kandasamy Yaoliang Yu 20 44 0 31 Jan 2016
Generalized Spectral Kernels Yves-Laurent Kom Samo Stephen J. Roberts 24 54 0 07 Jun 2015
Polynomial-Chaos-based Kriging R. Schöbi Bruno Sudret J. Wiart 38 269 0 13 Feb 2015
High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning Francis R. Bach BDL 126 74 0 04 Sep 2009