A Simple Baseline for Bayesian Uncertainty in Deep Learning

7 February 2019

Dmitry Vetrov

Papers citing "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

50 / 229 papers shown

Title
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 30 4 0 06 Apr 2023
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning Ildus Sadrtdinov Dmitrii Pozdeev Dmitry Vetrov E. Lobacheva 35 4 0 06 Mar 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 22 39 0 06 Mar 2023
Non-Parametric Outlier Synthesis Leitian Tao Xuefeng Du Xiaojin Zhu Yixuan Li OODD 28 98 0 06 Mar 2023
A Review of Uncertainty Estimation and its Application in Medical Imaging K. Zou Zhihao Chen Xuedong Yuan Xiaojing Shen Meng Wang Huazhu Fu UQCV 49 85 0 16 Feb 2023
Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets Marianne A Jonker H. Pazira Anthony C. C. Coolen FedML 28 5 0 15 Feb 2023
Probabilistic Circuits That Know What They Don't Know Fabrizio G. Ventola Steven Braun Zhongjie Yu Martin Mundt Kristian Kersting UQCV TPM 32 7 0 13 Feb 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 37 16 0 13 Feb 2023
Beyond In-Domain Scenarios: Robust Density-Aware Calibration Christian Tomani Futa Waseda Yuesong Shen Daniel Cremers UQCV 37 4 0 10 Feb 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 39 35 0 10 Feb 2023
Joint Training of Deep Ensembles Fails Due to Learner Collusion Alan Jeffares Tennison Liu Jonathan Crabbé M. Schaar FedML 56 15 0 26 Jan 2023
Uncertainty Estimation based on Geometric Separation Gabriella Chouraqui L. Cohen Gil Einziger Liel Leman 35 0 0 11 Jan 2023
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective Wenbo Shao Yan Xu Liang Peng Jun Li Hong Wang 34 15 0 11 Jan 2023
Do Bayesian Variational Autoencoders Know What They Don't Know? Misha Glazunov Apostolis Zarras UQCV BDL 28 5 0 29 Dec 2022
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning Wenxuan Ma Xing Yan Kun Zhang UQCV 28 0 0 24 Dec 2022
Uncertainty in Real-Time Semantic Segmentation on Embedded Systems Ethan Goan Clinton Fookes UQCV 31 4 0 20 Dec 2022
A Probabilistic Framework for Lifelong Test-Time Adaptation Dhanajit Brahma Piyush Rai TTA 24 35 0 19 Dec 2022
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig Hampus Linander BDL UQCV 29 5 0 15 Dec 2022
Investigating Deep Learning Model Calibration for Classification Problems in Mechanics S. Mohammadzadeh Peerasait Prachaseree Emma Lejeune AI4CE 34 2 0 01 Dec 2022
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 37 7 0 01 Dec 2022
Non-reversible Parallel Tempering for Deep Posterior Approximation Wei Deng Qian Zhang Qi Feng F. Liang Guang Lin 26 4 0 20 Nov 2022
Layer-Stack Temperature Scaling Amr Khalifa Michael C. Mozer Hanie Sedghi Behnam Neyshabur Ibrahim M. Alabdulmohsin 81 2 0 18 Nov 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 23 52 0 11 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 39 3 0 03 Nov 2022
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier Alain Durmus Eric Moulines FedML 21 6 0 31 Oct 2022
On the optimization and pruning for Bayesian deep learning X. Ke Yanan Fan BDL UQCV 35 1 0 24 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 50 19 0 23 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation Olivier Laurent Adrien Lafage Enzo Tartaglione Geoffrey Daniel Jean-Marc Martinez Andrei Bursuc Gianni Franchi OODD 46 32 0 17 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 41 21 0 12 Oct 2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 31 80 0 05 Oct 2022
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning Seongok Ryu Sumin Lee 19 5 0 29 Sep 2022
Bayesian Neural Network Versus Ex-Post Calibration For Prediction Uncertainty Satya Borgohain Klaus Ackermann Rubén Loaiza-Maya BDL UQCV 18 0 0 29 Sep 2022
Strong Transferable Adversarial Attacks via Ensembled Asymptotically Normal Distribution Learning Zhengwei Fang Rui Wang Tao Huang L. Jing AAML 40 5 0 24 Sep 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup Zongbo Han Zhipeng Liang Fan Yang Liu Liu Lanqing Li Yatao Bian P. Zhao Bing Wu Changqing Zhang Jianhua Yao 56 34 0 19 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 32 4 0 17 Sep 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 255 318 0 11 Sep 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 25 34 0 05 Sep 2022
CUAHN-VIO: Content-and-Uncertainty-Aware Homography Network for Visual-Inertial Odometry Ying Xu Guido de Croon BDL 38 5 0 30 Aug 2022
OpenCon: Open-world Contrastive Learning Yiyou Sun Yixuan Li VLM SSL DRL 57 39 0 04 Aug 2022
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry M. Penrod Harrison Termotto Varshini Reddy Jiayu Yao Finale Doshi-Velez Weiwei Pan AAML OOD 43 1 0 02 Aug 2022
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs Emilia Magnani Nicholas Kramer Runa Eschenhagen Lorenzo Rosasco Philipp Hennig UQCV BDL 21 9 0 02 Aug 2022
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity Martin Gubri Maxime Cordy Mike Papadakis Yves Le Traon Koushik Sen AAML 35 51 0 26 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 62 71 0 19 Jul 2022
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation Victor Besnier Andrei Bursuc David Picard Alexandre Briot 39 1 0 18 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
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets Yingsong Huang Bing Bai Shengwei Zhao Kun Bai Fei Wang NoLa 30 44 0 12 Jul 2022
Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models Yizhe Zhang Suraj Mishra Peixian Liang Hao Zheng Danny Chen 14 3 0 01 Jul 2022
Laplacian Autoencoders for Learning Stochastic Representations M. Miani Frederik Warburg Pablo Moreno-Muñoz Nicke Skafte Detlefsen Søren Hauberg UQCV BDL SSL 41 10 0 30 Jun 2022
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier Bartosz Wójcik J. Grela Marek Śmieja Krzysztof Misztal Jacek Tabor UQCV 33 4 0 28 Jun 2022