Adapting the Linearised Laplace Model Evidence for Modern Deep Learning

17 June 2022

Javier Antorán

José Miguel Hernández-Lobato

UQCV

BDL

ArXiv PDF HTML

Papers citing "Adapting the Linearised Laplace Model Evidence for Modern Deep Learning"

26 / 26 papers shown

Title
Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis Sanket R. Jantre Tianle Wang Gilchan Park Kriti Chopra Nicholas Jeon Xiaoning Qian Nathan M. Urban Byung-Jun Yoon 57 0 0 10 Feb 2025
Reparameterization invariance in approximate Bayesian inference Hrittik Roy M. Miani Carl Henrik Ek Philipp Hennig Marvin Pfortner Lukas Tatzel Søren Hauberg BDL 39 8 0 05 Jun 2024
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Zeyu Han Chao Gao Jinyang Liu Jeff Zhang Sai Qian Zhang 139 301 0 21 Mar 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood Rayen Dhahri Alexander Immer Bertrand Charpentier Stephan Günnemann Vincent Fortuin BDL UQCV 22 4 0 25 Feb 2024
Bayesian Reward Models for LLM Alignment Adam X. Yang Maxime Robeyns Thomas Coste Zhengyan Shi Jun Wang Haitham Bou-Ammar Laurence Aitchison 32 17 0 20 Feb 2024
Active Few-Shot Fine-Tuning Jonas Hübotter Bhavya Sukhija Lenart Treven Yarden As Andreas Krause 28 1 0 13 Feb 2024
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 54 18 0 28 Sep 2023
Bayesian Low-rank Adaptation for Large Language Models Adam X. Yang Maxime Robeyns Xi Wang Laurence Aitchison AI4CE BDL 11 44 0 24 Aug 2023
Online Laplace Model Selection Revisited J. Lin Javier Antorán José Miguel Hernández-Lobato BDL 19 3 0 12 Jul 2023
Quantification of Uncertainty with Adversarial Models Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi G. Klambauer Sepp Hochreiter UQCV 21 13 0 06 Jul 2023
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent J. Lin Javier Antorán Shreyas Padhy David Janz José Miguel Hernández-Lobato Alexander Terenin 14 22 0 20 Jun 2023
Riemannian Laplace approximations for Bayesian neural networks Federico Bergamin Pablo Moreno-Muñoz Søren Hauberg Georgios Arvanitidis BDL 17 6 0 12 Jun 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels Alexander Immer Tycho F. A. van der Ouderaa Mark van der Wilk Gunnar Rätsch Bernhard Schölkopf BDL 22 11 0 06 Jun 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 19 6 0 26 May 2023
Image Reconstruction via Deep Image Prior Subspaces Riccardo Barbano Javier Antorán Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin vZeljko Kereta 18 1 0 20 Feb 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 11 10 0 14 Feb 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 21 16 0 13 Feb 2023
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 21 17 0 10 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 16 4 0 30 Sep 2022
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior Riccardo Barbano Johannes Leuschner Javier Antorán Bangti Jin José Miguel Hernández-Lobato 13 12 0 11 Jul 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 18 5 0 22 Jun 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 22 10 0 28 Feb 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 45 55 0 23 Feb 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 15 44 0 22 Feb 2022
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 220 510 0 11 Feb 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016