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 / 189 papers shown

Title
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective Wenbo Shao Yan Xu Liang Peng Jun Li Hong Wang 29 15 0 11 Jan 2023
Do Bayesian Variational Autoencoders Know What They Don't Know? Misha Glazunov Apostolis Zarras UQCV BDL 25 5 0 29 Dec 2022
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 27 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 27 7 0 01 Dec 2022
Layer-Stack Temperature Scaling Amr Khalifa Michael C. Mozer Hanie Sedghi Behnam Neyshabur Ibrahim M. Alabdulmohsin 78 2 0 18 Nov 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 18 52 0 11 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 28 3 0 03 Nov 2022
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier Alain Durmus Eric Moulines FedML 14 6 0 31 Oct 2022
On the optimization and pruning for Bayesian deep learning X. Ke Yanan Fan BDL UQCV 27 1 0 24 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 47 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 44 32 0 17 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 30 21 0 12 Oct 2022
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning Seongok Ryu Sumin Lee 16 5 0 29 Sep 2022
Bayesian Neural Network Versus Ex-Post Calibration For Prediction Uncertainty Satya Borgohain Klaus Ackermann Rubén Loaiza-Maya BDL UQCV 13 0 0 29 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 53 34 0 19 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 30 4 0 17 Sep 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 252 314 0 11 Sep 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 22 34 0 05 Sep 2022
CUAHN-VIO: Content-and-Uncertainty-Aware Homography Network for Visual-Inertial Odometry Ying Xu Guido de Croon BDL 33 5 0 30 Aug 2022
OpenCon: Open-world Contrastive Learning Yiyou Sun Yixuan Li VLM SSL DRL 44 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 37 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 13 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 27 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 54 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
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks Uddeshya Upadhyay Shyamgopal Karthik Yanbei Chen Massimiliano Mancini Zeynep Akata UQCV BDL 32 22 0 14 Jul 2022
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets Yingsong Huang Bing Bai Shengwei Zhao Kun Bai Fei-Yue Wang NoLa 23 43 0 12 Jul 2022
Laplacian Autoencoders for Learning Stochastic Representations M. Miani Frederik Warburg Pablo Moreno-Muñoz Nicke Skafte Detlefsen Søren Hauberg UQCV BDL SSL 30 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
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
Personalized Federated Learning via Variational Bayesian Inference Xu Zhang Yinchuan Li Wenpeng Li Kaiyang Guo Yunfeng Shao FedML 43 85 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 42 6 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 19 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 18 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
The Unreasonable Effectiveness of Deep Evidential Regression N. Meinert J. Gawlikowski Alexander Lavin UQCV EDL 177 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 32 3 0 16 May 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder Yaniv Romano Matteo Sesia Yanfei Zhou UQCV 23 48 0 12 May 2022
Norm-Scaling for Out-of-Distribution Detection Deepak Ravikumar Kaushik Roy OODD UQCV 19 2 0 06 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 16 18 0 30 Apr 2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation Maria De-Arteaga Alexandra Chouldechova Artur Dubrawski 27 4 0 29 Apr 2022
The Sillwood Technologies System for the VoiceMOS Challenge 2022 Jiameng Gao 18 0 0 08 Apr 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation Yassir Fathullah Mark J. F. Gales UQCV 14 11 0 15 Mar 2022
Scalable Uncertainty Quantification for Deep Operator Networks using Randomized Priors Yibo Yang Georgios Kissas P. Perdikaris BDL UQCV 22 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 23 28 0 02 Mar 2022
Non-Volatile Memory Accelerated Posterior Estimation A. Wood Moshik Hershcovitch Daniel Waddington Sarel Cohen Peter Chin 13 1 0 21 Feb 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 26 10 0 20 Feb 2022