Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks

24 February 2020

Matthias Hein

Papers citing "Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks"

50 / 55 papers shown

Title
Uncertainty-aware Bayesian machine learning modelling of land cover classification Samuel Bilson Anna Pustogvar UQCV 89 1 0 27 Mar 2025
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble Jacopo Talpini Marco Savi Giovanni Neglia FedML Presented at ResearchTrend Connect \| FedML on 07 May 2025 76 0 0 19 Mar 2025
EvidMTL: Evidential Multi-Task Learning for Uncertainty-Aware Semantic Surface Mapping from Monocular RGB Images Rohit Menon Nils Dengler Sicong Pan Gokul Krishna Chenchani Maren Bennewitz EDL 88 0 0 06 Mar 2025
Optimizing Estimators of Squared Calibration Errors in Classification Sebastian G. Gruber Francis Bach 69 1 0 24 Feb 2025
Making Reliable and Flexible Decisions in Long-tailed Classification Bolian Li Ruqi Zhang 137 0 0 23 Jan 2025
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 91 2 0 27 Nov 2024
Fine-Grained Uncertainty Quantification via Collisions Jesse Friedbaum S. Adiga Ravi Tandon 69 0 0 18 Nov 2024
Debiasing Mini-Batch Quadratics for Applications in Deep Learning Lukas Tatzel Bálint Mucsányi Osane Hackel Philipp Hennig 43 0 0 18 Oct 2024
Manifold Sampling for Differentiable Uncertainty in Radiance Fields Linjie Lyu Ayush Tewari Marc Habermann Shunsuke Saito Michael Zollhöfer Thomas Leimkühler Christian Theobalt UQCV 38 1 0 19 Sep 2024
Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani Marvin Pfortner Tobias Weber Philipp Hennig UQCV 63 1 0 07 Jun 2024
Reparameterization invariance in approximate Bayesian inference Hrittik Roy M. Miani Carl Henrik Ek Philipp Hennig Marvin Pfortner Lukas Tatzel Søren Hauberg BDL 42 8 0 05 Jun 2024
Gradients of Functions of Large Matrices Nicholas Krämer Pablo Moreno-Muñoz Hrittik Roy Søren Hauberg 32 0 0 27 May 2024
LoRA Dropout as a Sparsity Regularizer for Overfitting Control Yang Lin Xinyu Ma Xu Chu Yujie Jin Zhibang Yang Yasha Wang Hong-yan Mei 46 19 0 15 Apr 2024
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex Yasushi Esaki Akihiro Nakamura Keisuke Kawano Ryoko Tokuhisa Takuro Kutsuna 38 0 0 21 Feb 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 79 7 0 12 Feb 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Philipp Reiser Javier Enrique Aguilar A. Guthke Paul-Christian Burkner 36 2 0 08 Dec 2023
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions Shiyu Shen Bin Pan Tianyang Shi Tao Li Zhenwei Shi BDL OOD 21 1 0 25 Oct 2023
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference Siqi Kou Lei Gan Dequan Wang Chongxuan Li Zhijie Deng BDL DiffM 21 7 0 17 Oct 2023
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 16 1 0 11 Aug 2023
Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network Rebecca S Stone Nishant Ravikumar A. Bulpitt David C. Hogg BDL 34 0 0 29 Mar 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 26 16 0 13 Feb 2023
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows Line C. Pouchard Kristofer G. Reyes Francis J. Alexander Byung-Jun Yoon 27 2 0 13 Jan 2023
Data-driven Science and Machine Learning Methods in Laser-Plasma Physics Andreas Döpp C. Eberle S. Howard F. Irshad Jinpu Lin M. Streeter AI4CE 24 63 0 30 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 26 3 0 03 Nov 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 44 19 0 23 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 24 4 0 30 Sep 2022
Bayesian Continual Learning via Spiking Neural Networks N. Skatchkovsky Hyeryung Jang Osvaldo Simeone BDL 30 17 0 29 Aug 2022
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs Emilia Magnani Nicholas Kramer Runa Eschenhagen Lorenzo Rosasco Philipp Hennig UQCV BDL 13 9 0 02 Aug 2022
Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks Sérgio A. Balanya Juan Maroñas Daniel Ramos OOD 35 13 0 31 Jul 2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration Thomas Joy Francesco Pinto Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 19 30 0 13 Jul 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 27 34 0 29 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 25 28 0 17 Jun 2022
Test-Time Adaptation for Visual Document Understanding Sayna Ebrahimi Sercan Ö. Arik Tomas Pfister OOD 31 6 0 15 Jun 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 48 0 01 May 2022
Multi-model Ensemble Analysis with Neural Network Gaussian Processes Trevor Harris B. Li Ryan Sriver 16 5 0 08 Feb 2022
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 21 2 0 12 Dec 2021
Probabilistic Approach for Road-Users Detection Gledson Melotti Weihao Lu Pedro Conde Dezong Zhao A. Asvadi Nuno Gonçalves C. Premebida 19 2 0 02 Dec 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 28 80 0 26 Oct 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 31 9 0 08 Oct 2021
Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark S. Dubey S. Singh B. B. Chaudhuri 30 640 0 29 Sep 2021
Who's Afraid of Thomas Bayes? Erick Galinkin AAML 20 0 0 30 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 30 1,109 0 07 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 33 288 0 28 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 15 15 0 18 Jun 2021
Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra Kanil Patel William H. Beluch K. Rambach Adriana-Eliza Cozma Michael Pfeiffer Bin Yang EDL UQCV 14 5 0 01 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty Zehao Xiao Jiayi Shen Xiantong Zhen Ling Shao Cees G. M. Snoek BDL UQCV OOD 29 39 0 09 May 2021
Sparse-shot Learning with Exclusive Cross-Entropy for Extremely Many Localisations Andreas Panteli Jonas Teuwen H. Horlings E. Gavves 21 3 0 21 Apr 2021
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty Chao Qu Wenxin Liu Camillo J. Taylor UQCV BDL 17 31 0 29 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip H. S. Torr Y. Gal UD UQCV PER BDL 18 145 0 23 Feb 2021