Laplace Redux -- Effortless Bayesian Deep Learning

28 June 2021

Papers citing "Laplace Redux -- Effortless Bayesian Deep Learning"

50 / 211 papers shown

Title
Deep equilibrium models as estimators for continuous latent variables Russell Tsuchida Cheng Soon Ong 30 8 0 11 Nov 2022
Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics Hany Abdulsamad Peter Nickl Pascal Klink Jan Peters 21 0 0 02 Nov 2022
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer Andrius Ovsianas Jason Ramapuram Dan Busbridge Eeshan Gunesh Dhekane Russ Webb 16 4 0 28 Oct 2022
On double-descent in uncertainty quantification in overparametrized models Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová UQCV 46 12 0 23 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 47 19 0 23 Oct 2022
Uncertainty estimation for out-of-distribution detection in computational histopathology Lea Goetz OOD 24 0 0 18 Oct 2022
Efficient Bayesian Updates for Deep Learning via Laplace Approximations Denis Huseljic M. Herde Lukas Rauch Paul Hahn Zhixin Huang D. Kottke S. Vogt Bernhard Sick BDL 16 0 0 12 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 27 17 0 10 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 26 4 0 30 Sep 2022
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 33 4 0 29 Sep 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? Lisa Wimmer Yusuf Sale Paul Hofman Bern Bischl Eyke Hüllermeier PER UD 36 64 0 07 Sep 2022
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs Emilia Magnani Nicholas Kramer Runa Eschenhagen Lorenzo Rosasco Philipp Hennig UQCV BDL 15 9 0 02 Aug 2022
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities Andreas Kirsch Y. Gal FedML 29 21 0 01 Aug 2022
Towards Clear Expectations for Uncertainty Estimation Victor Bouvier Simona Maggio A. Abraham L. Dreyfus-Schmidt UQCV 28 1 0 27 Jul 2022
Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors Gianluca Detommaso Alberto Gasparin A. Wilson Cédric Archambeau UQCV BDL 34 3 0 17 Jul 2022
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks Uddeshya Upadhyay Shyamgopal Karthik Yanbei Chen Massimiliano Mancini Zeynep Akata UQCV BDL 35 22 0 14 Jul 2022
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies E. Small Wei Shao Zeliang Zhang Peihan Liu Jeffrey Chan Kacper Sokol Flora D. Salim 57 2 0 11 Jul 2022
Challenges and Pitfalls of Bayesian Unlearning Ambrish Rawat James Requeima W. Bruinsma Richard Turner BDL MU 44 5 0 07 Jul 2022
Laplacian Autoencoders for Learning Stochastic Representations M. Miani Frederik Warburg Pablo Moreno-Muñoz Nicke Skafte Detlefsen Søren Hauberg UQCV BDL SSL 35 10 0 30 Jun 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 14 4 0 24 Jun 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 23 5 0 22 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 27 28 0 17 Jun 2022
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift Andreas Klass Sven M. Lorenz M. Lauer-Schmaltz David Rügamer Bernd Bischl Christopher Mutschler Felix Ott 31 10 0 17 Jun 2022
Benchmarking Bayesian neural networks and evaluation metrics for regression tasks B. Staber Sébastien Da Veiga UQCV BDL 42 3 0 08 Jun 2022
Functional Ensemble Distillation Coby Penso Idan Achituve Ethan Fetaya FedML 33 2 0 05 Jun 2022
Understanding Deep Learning via Decision Boundary Shiye Lei Fengxiang He Yancheng Yuan Dacheng Tao 17 13 0 03 Jun 2022
Laplace HypoPINN: Physics-Informed Neural Network for hypocenter localization and its predictive uncertainty M. Izzatullah I. Yildirim U. Waheed T. Alkhalifah 33 16 0 28 May 2022
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed Mélanie Bernhardt Fabio De Sousa Ribeiro Ben Glocker 26 10 0 27 May 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 21 12 0 20 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 21 48 0 01 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 24 18 0 30 Apr 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Daubener Asja Fischer SILM AAML 20 1 0 22 Apr 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 26 48 0 30 Mar 2022
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 23 34 0 17 Mar 2022
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference Luca Rendsburg Agustinus Kristiadi Philipp Hennig U. V. Luxburg 16 2 0 07 Mar 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 24 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 52 56 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 39 44 0 22 Feb 2022
Augmenting Neural Networks with Priors on Function Values Hunter Nisonoff Yixin Wang Jennifer Listgarten 23 3 0 10 Feb 2022
Theoretical characterization of uncertainty in high-dimensional linear classification Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová 36 20 0 07 Feb 2022
Multimodal Maximum Entropy Dynamic Games Oswin So Kyle Stachowicz Evangelos A. Theodorou 28 7 0 30 Jan 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization Frederik Benzing ODL 43 23 0 28 Jan 2022
Analytic Mutual Information in Bayesian Neural Networks J. Woo UQCV 25 6 0 24 Jan 2022
Efficient Online Bayesian Inference for Neural Bandits Gerardo Duran-Martín Aleyna Kara Kevin Patrick Murphy BDL 19 13 0 01 Dec 2021
Merging Models with Fisher-Weighted Averaging Michael Matena Colin Raffel FedML MoMe 32 352 0 18 Nov 2021
Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning Runa Eschenhagen Erik A. Daxberger Philipp Hennig Agustinus Kristiadi UQCV BDL 30 22 0 05 Nov 2021
Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization Dinesh Singh Hardik Tankaria M. Yamada ODL 42 2 0 16 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 48 48 0 06 Oct 2021
Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization K. Cohen Sangwoo Park Osvaldo Simeone S. Shamai 23 12 0 02 Aug 2021
ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure Felix Dangel Lukas Tatzel Philipp Hennig 24 12 0 04 Jun 2021