Transforming Gaussian Processes With Normalizing Flows

Transforming Gaussian Processes With Normalizing Flows

3 November 2020

Oliver Hamelijnck

Jeremias Knoblauch

Theodoros Damoulas

Papers citing "Transforming Gaussian Processes With Normalizing Flows"

11 / 11 papers shown

Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 54 0 0 24 Mar 2025
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 23 10 0 01 Nov 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space Model Zhidi Lin Feng Yin Juan Maroñas 34 7 0 21 Jan 2023
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification Juan Maroñas Daniel Hernández-Lobato 17 6 0 30 May 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A. Maraval Matthieu Zimmer Antoine Grosnit Rasul Tutunov Jun Wang H. Ammar 30 2 0 27 May 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation Emma R. Cobian J. Hauenstein Fang Liu Daniele E. Schiavazzi 19 4 0 01 Feb 2022
Non-Gaussian Gaussian Processes for Few-Shot Regression Marcin Sendera Jacek Tabor A. Nowak Andrzej Bedychaj Massimiliano Patacchiola Tomasz Trzciñski P. Spurek Maciej Ziȩba 18 19 0 26 Oct 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation Alexander I. Cowen-Rivers Wenlong Lyu Rasul Tutunov Zhi Wang Antoine Grosnit ... A. Maraval Hao Jianye Jun Wang Jan Peters H. Ammar 27 74 0 07 Dec 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 89 271 0 24 Feb 2014