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"

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Title
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 37 10 0 17 Jun 2022
Personalized Federated Learning via Variational Bayesian Inference Xu Zhang Yinchuan Li Wenpeng Li Kaiyang Guo Yunfeng Shao FedML 51 86 0 16 Jun 2022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling Jiri Hron Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 48 6 0 15 Jun 2022
Federated Learning with Uncertainty via Distilled Predictive Distributions Shreyansh P. Bhatt Aishwarya Gupta Piyush Rai FedML 29 11 0 15 Jun 2022
Which models are innately best at uncertainty estimation? Ido Galil Mohammed Dabbah Ran El-Yaniv UQCV 34 5 0 05 Jun 2022
LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection Matthew A. Pitropov Chengjie Huang Vahdat Abdelzad Krzysztof Czarnecki Steven Waslander 3DPC 21 3 0 01 Jun 2022
Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance? Christoph Koller Goran Kauermann Xiao Xiang Zhu UQCV 24 6 0 30 May 2022
Split personalities in Bayesian Neural Networks: the case for full marginalisation David Yallup Will Handley Michael P. Hobson A. Lasenby Pablo Lemos 25 1 0 23 May 2022
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv Micah Goldblum Hossein Souri Sanyam Kapoor Chen Zhu Yann LeCun A. Wilson UQCV BDL 64 43 0 20 May 2022
The Unreasonable Effectiveness of Deep Evidential Regression N. Meinert J. Gawlikowski Alexander Lavin UQCV EDL 192 35 0 20 May 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks Sai Munikoti D. Agarwal Laya Das Balasubramaniam Natarajan BDL UD 31 13 0 20 May 2022
Robust Representation via Dynamic Feature Aggregation Haozhe Liu Haoqin Ji Yuexiang Li Nanjun He Haoqian Wu Feng Liu Linlin Shen Yefeng Zheng AAML OOD 34 3 0 16 May 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder Yaniv Romano Matteo Sesia Yanfei Zhou UQCV 29 49 0 12 May 2022
Norm-Scaling for Out-of-Distribution Detection Deepak Ravikumar Kaushik Roy OODD UQCV 24 2 0 06 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 27 18 0 30 Apr 2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation Maria De-Arteaga Alexandra Chouldechova Artur Dubrawski 33 4 0 29 Apr 2022
The Sillwood Technologies System for the VoiceMOS Challenge 2022 Jiameng Gao 30 0 0 08 Apr 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation Yassir Fathullah Mark Gales UQCV 22 11 0 15 Mar 2022
Scalable Uncertainty Quantification for Deep Operator Networks using Randomized Priors Yibo Yang Georgios Kissas P. Perdikaris BDL UQCV 35 40 0 06 Mar 2022
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks Gianni Franchi Xuanlong Yu Andrei Bursuc Ángel Tena Rémi Kazmierczak Séverine Dubuisson Emanuel Aldea David Filliat UQCV 26 28 0 02 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 37 10 0 28 Feb 2022
Parallel MCMC Without Embarrassing Failures Daniel Augusto R. M. A. de Souza Diego Mesquita Samuel Kaski Luigi Acerbi 42 11 0 22 Feb 2022
Non-Volatile Memory Accelerated Posterior Estimation A. Wood Moshik Hershcovitch Daniel Waddington Sarel Cohen Peter Chin 16 1 0 21 Feb 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 43 10 0 20 Feb 2022
Deep Ensembles Work, But Are They Necessary? Taiga Abe E. Kelly Buchanan Geoff Pleiss R. Zemel John P. Cunningham OOD UQCV 44 60 0 14 Feb 2022
PFGE: Parsimonious Fast Geometric Ensembling of DNNs Hao Guo Jiyong Jin B. Liu FedML 32 1 0 14 Feb 2022
Model Architecture Adaption for Bayesian Neural Networks Duo Wang Yiren Zhao Ilia Shumailov Robert D. Mullins UQCV OOD BDL 26 0 0 09 Feb 2022
Lymphoma segmentation from 3D PET-CT images using a deep evidential network Ling Huang S. Ruan P. Decazes Thierry Denoeux 3DPC MedIm 41 37 0 31 Jan 2022
Stochastic Neural Networks with Infinite Width are Deterministic Liu Ziyin Hanlin Zhang Xiangming Meng Yuting Lu Eric P. Xing Masakuni Ueda 34 3 0 30 Jan 2022
Improving robustness and calibration in ensembles with diversity regularization H. A. Mehrtens Camila González Anirban Mukhopadhyay UQCV 19 7 0 26 Jan 2022
GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting Zhao Chen Vincent Casser Henrik Kretzschmar Dragomir Anguelov 31 5 0 16 Jan 2022
SpectraNet: Learned Recognition of Artificial Satellites From High Contrast Spectroscopic Imagery J. Gazak Ian McQuaid R. Swindle M. Phelps Justin Fletcher 29 14 0 10 Jan 2022
Model-Value Inconsistency as a Signal for Epistemic Uncertainty Angelos Filos Eszter Vértes Zita Marinho Gregory Farquhar Diana Borsa A. Friesen Feryal M. P. Behbahani Tom Schaul André Barreto Simon Osindero 44 7 0 08 Dec 2021
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting Abdulmajid Murad F. Kraemer Kerstin Bach Gavin Taylor OOD BDL UQCV 20 12 0 05 Dec 2021
Toward Practical Monocular Indoor Depth Estimation Cho-Ying Wu Jialiang Wang Michael Hall Ulrich Neumann Shuochen Su 3DV MDE 45 63 0 04 Dec 2021
Exploring Segment-level Semantics for Online Phase Recognition from Surgical Videos Xinpeng Ding Xiaomeng Li 22 33 0 22 Nov 2021
Deep Probability Estimation Sheng Liu Aakash Kaku Weicheng Zhu M. Leibovich S. Mohan ... Haoxiang Huang L. Zanna N. Razavian Jonathan Niles-Weed C. Fernandez‐Granda UQCV OOD 28 14 0 21 Nov 2021
DICE: Leveraging Sparsification for Out-of-Distribution Detection Yiyou Sun Yixuan Li OODD 38 151 0 18 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 29 58 0 03 Nov 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 81 0 26 Oct 2021
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification Romain Egele R. Maulik Krishnan Raghavan Bethany Lusch Isabelle M Guyon Prasanna Balaprakash UQCV OOD BDL 20 47 0 26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 193 879 0 21 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning Ching-Hsun Tseng Liu Cheng Shin-Jye Lee Xiaojun Zeng 45 5 0 01 Oct 2021
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation Robin Camarasa D. Bos J. Hendrikse P. Nederkoorn D. Epidemiology D. Neurology Department of Computer Science UQCV 26 12 0 22 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 24 18 0 16 Sep 2021
Fair Conformal Predictors for Applications in Medical Imaging Charles Lu A. Lemay Ken Chang K. Hoebel Jayashree Kalpathy-Cramer MedIm 20 67 0 09 Sep 2021
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations Jianxiong Shen Adria Ruiz Antonio Agudo Francesc Moreno-Noguer BDL 36 68 0 05 Sep 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 34 25 0 23 Aug 2021
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation Victor Besnier Andrei Bursuc David Picard Alexandre Briot UQCV 24 48 0 03 Aug 2021
Batch Normalization Preconditioning for Neural Network Training Susanna Lange Kyle E. Helfrich Qiang Ye 27 9 0 02 Aug 2021