Dual Parameterization of Sparse Variational Gaussian Processes

Dual Parameterization of Sparse Variational Gaussian Processes

5 November 2021

Mohammad Emtiyaz Khan

Arno Solin

Papers citing "Dual Parameterization of Sparse Variational Gaussian Processes"

14 / 14 papers shown

Title
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems Amber Hu D. Zoltowski Aditya Nair David Anderson Lea Duncker Scott W. Linderman 36 3 0 19 Jul 2024
One-Shot Federated Learning with Bayesian Pseudocoresets Tim d'Hondt Mykola Pechenizkiy Robert Peharz FedML 37 0 0 04 Jun 2024
Function-space Parameterization of Neural Networks for Sequential Learning Aidan Scannell Riccardo Mereu Paul E. Chang Ella Tamir Joni Pajarinen Arno Solin BDL 34 5 0 16 Mar 2024
Sparse Function-space Representation of Neural Networks Aidan Scannell Riccardo Mereu Paul E. Chang Ella Tamir Joni Pajarinen Arno Solin BDL 35 1 0 05 Sep 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models Rui Li S. T. John Arno Solin BDL 20 3 0 07 Jun 2023
Memory-Based Dual Gaussian Processes for Sequential Learning Paul E. Chang Prakhar Verma S. T. John Arno Solin Mohammad Emtiyaz Khan GP 25 4 0 06 Jun 2023
Variational Gaussian Process Diffusion Processes Prakhar Verma Vincent Adam Arno Solin DiffM 22 5 0 03 Jun 2023
Towards Improved Learning in Gaussian Processes: The Best of Two Worlds Rui Li S. T. John Arno Solin BDL GP 22 0 0 11 Nov 2022
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning Paul E. Chang Prakhar Verma S. T. John Victor Picheny Henry B. Moss Arno Solin GP 33 6 0 02 Nov 2022
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees Alexander Terenin David R. Burt A. Artemev Seth Flaxman Mark van der Wilk C. Rasmussen Hong Ge 58 7 0 14 Oct 2022
Sampling-based inference for large linear models, with application to linearised Laplace Javier Antorán Shreyas Padhy Riccardo Barbano Eric T. Nalisnick David Janz José Miguel Hernández-Lobato BDL 27 17 0 10 Oct 2022
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 21 15 0 02 Nov 2021
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 40 94 0 02 Mar 2020
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 268 0 13 Jun 2018