Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2011.01596
Cited By
v1
v2 (latest)
Transforming Gaussian Processes With Normalizing Flows
3 November 2020
Juan Maroñas
Oliver Hamelijnck
Jeremias Knoblauch
Theodoros Damoulas
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Transforming Gaussian Processes With Normalizing Flows"
17 / 17 papers shown
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
Zhidi Lin
Ying Li
Feng Yin
Juan Maroñas
Alexandre Thiéry
653
1
0
24 Mar 2025
Stochastic Process Learning via Operator Flow Matching
Yaozhong Shi
Zachary E. Ross
D. Asimaki
Kamyar Azizzadenesheli
694
8
0
07 Jan 2025
Variational Elliptical Processes
Maria B˙ankestad
Jens Sjölund
Jalil Taghia
Thomas B. Schon
344
3
0
21 Nov 2023
Robust and Conjugate Gaussian Process Regression
International Conference on Machine Learning (ICML), 2023
Matias Altamirano
F. Briol
Jeremias Knoblauch
408
16
0
01 Nov 2023
Deep Transformed Gaussian Processes
Francisco Javier Sáez-Maldonado
Juan Maroñas
Daniel Hernández-Lobato
400
0
0
27 Oct 2023
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Zhidi Lin
Juan Maroñas
Ying Li
Feng Yin
Sergios Theodoridis
335
3
0
03 Sep 2023
Kernelised Normalising Flows
International Conference on Learning Representations (ICLR), 2023
Eshant English
Matthias Kirchler
Christoph Lippert
TPM
408
0
0
27 Jul 2023
Deep Stochastic Processes via Functional Markov Transition Operators
Neural Information Processing Systems (NeurIPS), 2023
Jin Xu
Emilien Dupont
Kaspar Martens
Tom Rainforth
Yee Whye Teh
291
7
0
24 May 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space Model
Zhidi Lin
Feng Yin
Juan Maroñas
447
7
0
21 Jan 2023
Generative structured normalizing flow Gaussian processes applied to spectroscopic data
Natalie Klein
N. Panda
P. Gasda
Diane Oyen
169
1
0
14 Dec 2022
Statistical Deep Learning for Spatial and Spatio-Temporal Data
Annual Review of Statistics and Its Application (ARSIA), 2022
C. Wikle
A. Zammit‐Mangion
BDL
343
67
0
05 Jun 2022
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification
International Conference on Machine Learning (ICML), 2022
Juan Maroñas
Daniel Hernández-Lobato
371
9
0
30 May 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates
A. Maraval
Matthieu Zimmer
Antoine Grosnit
Rasul Tutunov
Jun Wang
H. Ammar
203
3
0
27 May 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
International Journal for Uncertainty Quantification (IJUQ), 2022
Emma R. Cobian
J. Hauenstein
Fang Liu
Daniele E. Schiavazzi
179
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
Przemysław Spurek
Maciej Ziȩba
260
21
0
26 Oct 2021
Priors in Bayesian Deep Learning: A Review
International Statistical Review (ISR), 2021
Vincent Fortuin
UQCV
BDL
548
166
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
529
118
0
07 Dec 2020
1
Page 1 of 1
