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2011.09421
Cited By
Understanding Variational Inference in Function-Space
18 November 2020
David R. Burt
Sebastian W. Ober
Adrià Garriga-Alonso
Mark van der Wilk
BDL
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Papers citing
"Understanding Variational Inference in Function-Space"
33 / 33 papers shown
Feed Two Birds with One Scone: Exploiting Function-Space Regularization for Both OOD Robustness and ID Fine-Tuning Performance
Xiang Yuan
Jun Shu
Deyu Meng
Zongben Xu
AAML
144
0
0
31 Aug 2025
Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel G. Müller
Arik Reuter
Noah Hollmann
David Rügamer
Katharina Eggensperger
324
9
0
29 May 2025
Variational Deep Learning via Implicit Regularization
Jonathan Wenger
Beau Coker
Juraj Marusic
John P. Cunningham
OOD
UQCV
FedML
350
1
0
26 May 2025
Bayes' Power for Explaining In-Context Learning Generalizations
Samuel G. Müller
Noah Hollmann
Katharina Eggensperger
BDL
229
5
0
02 Oct 2024
Functional Stochastic Gradient MCMC for Bayesian Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Mengjing Wu
Junyu Xuan
Jie Lu
BDL
356
2
0
25 Sep 2024
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks
Tristan Cinquin
Kushagra Pandey
UQCV
BDL
571
4
0
06 Jun 2024
One-Shot Federated Learning with Bayesian Pseudocoresets
Tim d'Hondt
Mykola Pechenizkiy
Robert Peharz
FedML
340
0
0
04 Jun 2024
Spectral Convolutional Conditional Neural Processes
Peiman Mohseni
Nick Duffield
380
4
0
19 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms
Ziyu Wang
Chris Holmes
UQCV
338
3
0
28 Mar 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou
Maria Skoularidou
Konstantina Palla
Laurence Aitchison
Julyan Arbel
...
David Rügamer
Yee Whye Teh
Max Welling
Andrew Gordon Wilson
Ruqi Zhang
UQCV
BDL
478
63
0
01 Feb 2024
Continual Learning via Sequential Function-Space Variational Inference
Tim G. J. Rudner
Freddie Bickford-Smith
Qixuan Feng
Yee Whye Teh
Y. Gal
293
55
0
28 Dec 2023
Tractable Function-Space Variational Inference in Bayesian Neural Networks
Tim G. J. Rudner
Zonghao Chen
Yee Whye Teh
Y. Gal
339
60
0
28 Dec 2023
Function-Space Regularization in Neural Networks: A Probabilistic Perspective
Tim G. J. Rudner
Sanyam Kapoor
Shikai Qiu
A. Wilson
242
23
0
28 Dec 2023
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Neural Information Processing Systems (NeurIPS), 2023
Balhae Kim
Hyungi Lee
Juho Lee
BDL
227
3
0
27 Oct 2023
Function-Space Regularization for Deep Bayesian Classification
J. Lin
Joe Watson
Pascal Klink
Jan Peters
UQCV
BDL
238
1
0
12 Jul 2023
Globally injective and bijective neural operators
Neural Information Processing Systems (NeurIPS), 2023
Takashi Furuya
Michael Puthawala
Matti Lassas
Maarten V. de Hoop
282
14
0
06 Jun 2023
Incorporating Unlabelled Data into Bayesian Neural Networks
Mrinank Sharma
Tom Rainforth
Yee Whye Teh
Vincent Fortuin
SSL
UQCV
BDL
342
10
0
04 Apr 2023
Random Grid Neural Processes for Parametric Partial Differential Equations
International Conference on Machine Learning (ICML), 2023
Arnaud Vadeboncoeur
Ieva Kazlauskaite
Y. Papandreou
F. Cirak
Mark Girolami
Ömer Deniz Akyildiz
AI4CE
301
11
0
26 Jan 2023
Diffusion Generative Models in Infinite Dimensions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Gavin Kerrigan
Justin Ley
Padhraic Smyth
DiffM
423
50
0
01 Dec 2022
On the detrimental effect of invariances in the likelihood for variational inference
Neural Information Processing Systems (NeurIPS), 2022
Richard Kurle
R. Herbrich
Tim Januschowski
Bernie Wang
Jan Gasthaus
336
9
0
15 Sep 2022
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning
Neural Information Processing Systems (NeurIPS), 2022
Veit Wild
Robert Hu
Dino Sejdinovic
BDL
357
17
0
12 May 2022
Deep Ensemble as a Gaussian Process Approximate Posterior
Zhijie Deng
Feng Zhou
Jianfei Chen
Guoqiang Wu
Jun Zhu
UQCV
231
5
0
30 Apr 2022
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices
Computer Methods in Applied Mechanics and Engineering (CMAME), 2021
Jan Povala
Ieva Kazlauskaite
Eky Febrianto
F. Cirak
Mark Girolami
319
31
0
22 Oct 2021
Function-space Inference with Sparse Implicit Processes
Simón Rodríguez Santana
B. Zaldívar
Daniel Hernández-Lobato
257
13
0
14 Oct 2021
On out-of-distribution detection with Bayesian neural networks
Francesco DÁngelo
Christian Henning
BDL
UQCV
359
10
0
12 Oct 2021
Pre-trained Gaussian processes for Bayesian optimization
Zehao Wang
George E. Dahl
Kevin Swersky
Chansoo Lee
Zachary Nado
Justin Gilmer
Jasper Snoek
Zoubin Ghahramani
385
80
0
16 Sep 2021
Self-explaining variational posterior distributions for Gaussian Process models
Sarem Seitz
BDL
135
0
0
08 Sep 2021
A variational approximate posterior for the deep Wishart process
Neural Information Processing Systems (NeurIPS), 2021
Sebastian W. Ober
Laurence Aitchison
BDL
211
11
0
21 Jul 2021
Repulsive Deep Ensembles are Bayesian
Neural Information Processing Systems (NeurIPS), 2021
Francesco DÁngelo
Vincent Fortuin
UQCV
BDL
544
125
0
22 Jun 2021
On Stein Variational Neural Network Ensembles
Francesco DÁngelo
Vincent Fortuin
F. Wenzel
UQCV
BDL
313
31
0
20 Jun 2021
Meta-Learning Reliable Priors in the Function Space
Neural Information Processing Systems (NeurIPS), 2021
Jonas Rothfuss
Dominique Heyn
Jinfan Chen
Andreas Krause
313
30
0
06 Jun 2021
Priors in Bayesian Deep Learning: A Review
International Statistical Review (ISR), 2021
Vincent Fortuin
UQCV
BDL
550
167
0
14 May 2021
Bayesian Deep Learning via Subnetwork Inference
International Conference on Machine Learning (ICML), 2020
Erik A. Daxberger
Eric T. Nalisnick
J. Allingham
Javier Antorán
José Miguel Hernández-Lobato
UQCV
BDL
614
106
0
28 Oct 2020
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