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Reparameterization invariance in approximate Bayesian inference

5 June 2024

Søren Hauberg

Papers citing "Reparameterization invariance in approximate Bayesian inference"

39 / 39 papers shown

Title
On Local Posterior Structure in Deep Ensembles Mikkel Jordahn Jonas Vestergaard Jensen Mikkel N. Schmidt Michael Riis Andersen UQCV BDL OOD 135 0 0 17 Mar 2025
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 97 1 0 30 Oct 2024
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections M. Miani Hrittik Roy Søren Hauberg UQCV BDL 100 0 0 22 Oct 2024
Debiasing Mini-Batch Quadratics for Applications in Deep Learning Lukas Tatzel Bálint Mucsányi Osane Hackel Philipp Hennig 91 0 0 18 Oct 2024
Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks Gaël Gendron Michael Witbrock Gillian Dobbie CML BDL OOD 60 0 0 08 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 158 0 0 07 Oct 2024
Riemannian Laplace Approximation with the Fisher Metric Hanlin Yu Marcelo Hartmann Bernardo Williams Mark Girolami Arto Klami 78 3 0 05 Nov 2023
Riemannian Laplace approximations for Bayesian neural networks Federico Bergamin Pablo Moreno-Muñoz Søren Hauberg Georgios Arvanitidis BDL 72 7 0 12 Jun 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 50 14 0 14 Feb 2023
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval Frederik Warburg M. Miani Silas Brack Søren Hauberg UQCV BDL 30 7 0 02 Feb 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 64 55 0 11 Nov 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 62 19 0 23 Oct 2022
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 40 17 0 10 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 79 5 0 30 Sep 2022
Laplacian Autoencoders for Learning Stochastic Representations M. Miani Frederik Warburg Pablo Moreno-Muñoz Nicke Skafte Detlefsen Søren Hauberg UQCV BDL SSL 68 11 0 30 Jun 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 78 31 0 17 Jun 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization Simone Bombari Mohammad Hossein Amani Marco Mondelli 67 26 0 20 May 2022
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework Zhiyuan Li Tianhao Wang Sanjeev Arora MLT 107 105 0 13 Oct 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 221 315 0 28 Jun 2021
Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov Patrick K. Nicholson Sanae Lotfi A. Wilson OOD UQCV BDL 125 46 0 22 Jun 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Alexander Immer Matthias Bauer Vincent Fortuin Gunnar Rätsch Mohammad Emtiyaz Khan BDL UQCV 130 109 0 11 Apr 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks Quynh N. Nguyen Marco Mondelli Guido Montúfar 57 83 0 21 Dec 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 80 86 0 28 Oct 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant Chaoyue Liu Libin Zhu M. Belkin 116 143 0 02 Oct 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 88 289 0 24 Feb 2020
A Reparameterization-Invariant Flatness Measure for Deep Neural Networks Henning Petzka Linara Adilova Michael Kamp C. Sminchisescu ODL 39 8 0 29 Nov 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 75 144 0 17 Jul 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 108 125 0 05 Jun 2019
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks Samet Oymak Mahdi Soltanolkotabi 52 322 0 12 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 96 809 0 07 Feb 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 53 177 0 25 Dec 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 266 1,469 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 220 1,135 0 09 Nov 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 273 3,219 0 20 Jun 2018
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis Thomas George César Laurent Xavier Bouthillier Nicolas Ballas Pascal Vincent ODL 82 156 0 11 Jun 2018
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 135 774 0 15 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 91 327 0 23 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015