Disentangling the Roles of Curation, Data-Augmentation and the Prior in
the Cold Posterior Effect

Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect

11 June 2021

Gregor Bachmann

Sebastian Nowozin

Papers citing "Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect"

18 / 18 papers shown

Title
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim G. Nam Chulhee Yun Hongseok Yang Juho Lee BDL UQCV 52 0 0 02 Mar 2025
Evaluating Bayesian deep learning for radio galaxy classification Devina Mohan Anna M. M. Scaife UQCV BDL 39 1 0 28 May 2024
Can a Confident Prior Replace a Cold Posterior? Martin Marek Brooks Paige Pavel Izmailov UQCV BDL 24 4 0 02 Mar 2024
Variational Learning is Effective for Large Deep Networks Yuesong Shen Nico Daheim Bai Cong Peter Nickl Gian Maria Marconi ... Rio Yokota Iryna Gurevych Daniel Cremers Mohammad Emtiyaz Khan Thomas Möllenhoff 35 22 0 27 Feb 2024
If there is no underfitting, there is no Cold Posterior Effect Yijie Zhang Yi-Shan Wu Luis A. Ortega A. Masegosa UQCV 21 1 0 02 Oct 2023
The fine print on tempered posteriors Konstantinos Pitas Julyan Arbel 25 1 0 11 Sep 2023
Incorporating Unlabelled Data into Bayesian Neural Networks Mrinank Sharma Tom Rainforth Yee Whye Teh Vincent Fortuin SSL UQCV BDL 34 9 0 04 Apr 2023
Training, Architecture, and Prior for Deterministic Uncertainty Methods Bertrand Charpentier Chenxiang Zhang Stephan Günnemann UQCV OOD AI4CE 29 6 0 10 Mar 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 16 52 0 11 Nov 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 16 5 0 14 Oct 2022
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study Tom Huix Szymon Majewski Alain Durmus Eric Moulines Anna Korba BDL 8 6 0 08 Jul 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 9 4 0 24 Jun 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 21 5 0 22 Jun 2022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 72 8 0 27 May 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 21 48 0 30 Mar 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography Francisca Vasconcelos Bobby He Nalini Singh Yee Whye Teh BDL OOD UQCV 24 12 0 22 Feb 2022
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 14 37 0 10 Jun 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,453 0 23 Jan 2020