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 19 8 0 11 Nov 2022
Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics Hany Abdulsamad Peter Nickl Pascal Klink Jan Peters 11 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 11 4 0 28 Oct 2022
On double-descent in uncertainty quantification in overparametrized models Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová UQCV 31 12 0 23 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 42 19 0 23 Oct 2022
Uncertainty estimation for out-of-distribution detection in computational histopathology Lea Goetz OOD 19 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 11 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 19 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
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 14 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 15 63 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 6 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 17 21 0 01 Aug 2022
Towards Clear Expectations for Uncertainty Estimation Victor Bouvier Simona Maggio A. Abraham L. Dreyfus-Schmidt UQCV 14 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 29 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 8 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 34 2 0 11 Jul 2022
Challenges and Pitfalls of Bayesian Unlearning Ambrish Rawat James Requeima W. Bruinsma Richard E. Turner BDL MU 23 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 17 10 0 30 Jun 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 18 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 22 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 29 10 0 17 Jun 2022
Benchmarking Bayesian neural networks and evaluation metrics for regression tasks B. Staber Sébastien Da Veiga UQCV BDL 21 3 0 08 Jun 2022
Functional Ensemble Distillation Coby Penso Idan Achituve Ethan Fetaya FedML 12 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 20 15 0 28 May 2022
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed Mélanie Bernhardt Fabio De Sousa Ribeiro Ben Glocker 15 9 0 27 May 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 19 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 16 47 0 01 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 8 18 0 30 Apr 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Daubener Asja Fischer SILM AAML 15 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 13 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 15 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 11 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 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
Augmenting Neural Networks with Priors on Function Values Hunter Nisonoff Yixin Wang Jennifer Listgarten 13 3 0 10 Feb 2022
Theoretical characterization of uncertainty in high-dimensional linear classification Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová 14 20 0 07 Feb 2022
Multimodal Maximum Entropy Dynamic Games Oswin So Kyle Stachowicz Evangelos A. Theodorou 21 7 0 30 Jan 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization Frederik Benzing ODL 35 23 0 28 Jan 2022
Analytic Mutual Information in Bayesian Neural Networks J. Woo UQCV 14 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 24 347 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 17 22 0 05 Nov 2021
Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization Dinesh Singh Hardik Tankaria M. Yamada ODL 15 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 29 47 0 06 Oct 2021
Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization K. Cohen Sangwoo Park Osvaldo Simeone S. Shamai 8 12 0 02 Aug 2021
ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure Felix Dangel Lukas Tatzel Philipp Hennig 16 12 0 04 Jun 2021