Evidential Deep Learning to Quantify Classification Uncertainty

5 June 2018

Papers citing "Evidential Deep Learning to Quantify Classification Uncertainty"

37 / 487 papers shown

Title
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty Miguel A. B. Monteiro Loic Le Folgoc Daniel Coelho De Castro Nick Pawlowski Bernardo Marques Konstantinos Kamnitsas Mark van der Wilk Ben Glocker UQCV BDL 20 113 0 10 Jun 2020
Uncertainty-Aware Deep Classifiers using Generative Models Murat Sensoy Lance M. Kaplan Federico Cerutti Maryam Saleki UQCV OOD 17 73 0 07 Jun 2020
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis P. Poduval H. Loya A. Sethi BDL UQCV 12 2 0 24 May 2020
Amortized Bayesian model comparison with evidential deep learning Stefan T. Radev Marco D’Alessandro U. Mertens A. Voss Ullrich Kothe Paul-Christian Bürkner BDL 22 33 0 22 Apr 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks Siqi Liu A. Setio Florin-Cristian Ghesu Eli Gibson Sasa Grbic Bogdan Georgescu Dorin Comaniciu AAML OOD 31 40 0 08 Mar 2020
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning Yiming Sun Bing Cao Pengfei Zhu Q. Hu 19 238 0 05 Mar 2020
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery Zepeng Huo Arash Pakbin Xiaohan Chen N. Hurley Ye Yuan Xiaoning Qian Zhangyang Wang Shuai Huang B. Mortazavi HAI 19 11 0 03 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 76 31 0 02 Mar 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 36 38 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
Fine-grained Uncertainty Modeling in Neural Networks Rahul Soni Naresh Shah J. D. Moore UQCV 6 5 0 11 Feb 2020
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving Di Feng Yifan Cao Lars Rosenbaum Fabian Timm Klaus C. J. Dietmayer UQCV 3DPC 21 23 0 01 Feb 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 81 1,353 0 21 Oct 2019
Explainable AI for Intelligence Augmentation in Multi-Domain Operations Alun D. Preece Dave Braines Federico Cerutti T. Pham 9 15 0 16 Oct 2019
Quantifying Classification Uncertainty using Regularized Evidential Neural Networks Xujiang Zhao Yuzhe Ou Lance M. Kaplan Feng Chen Jin-Hee Cho EDL BDL UQCV 18 16 0 15 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation Theodoros Tsiligkaridis UQCV BDL 8 8 0 10 Oct 2019
Deep Evidential Regression Alexander Amini Wilko Schwarting A. Soleimany Daniela Rus EDL PER BDL UD UQCV 28 417 0 07 Oct 2019
Operational Calibration: Debugging Confidence Errors for DNNs in the Field Zenan Li Xiaoxing Ma Chang Xu Jingwei Xu Chun Cao Jian Lu 24 28 0 06 Oct 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 24 139 0 26 Sep 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 11 37 0 20 Aug 2019
Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations Andras Rozsa Terrance E. Boult AAML 20 18 0 07 Aug 2019
Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units L. Meegahapola Vengateswaran Subramaniam Lance M. Kaplan Archan Misra 12 2 0 05 Jul 2019
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment Florin-Cristian Ghesu Bogdan Georgescu Eli Gibson Sebastian Gündel M. Kalra Ramandeep Singh S. Digumarthy Sasa Grbic Dorin Comaniciu UQCV 12 45 0 18 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 30 295 0 04 Jun 2019
Bayesian Evidential Deep Learning with PAC Regularization Manuel Haussmann S. Gerwinn M. Kandemir UQCV EDL BDL 6 1 0 03 Jun 2019
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness A. Malinin Mark J. F. Gales UQCV AAML 21 172 0 31 May 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 8 528 0 27 May 2019
Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework Daniel Bauer L. Kuhnert L. Eckstein EDL 11 12 0 29 Mar 2019
BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors Ali Harakeh Michael H. W. Smart Steven L. Waslander BDL UQCV 24 115 0 09 Mar 2019
A Variational Dirichlet Framework for Out-of-Distribution Detection Wenhu Chen Yilin Shen Xin Eric Wang Luu Anh Tuan UQCV 22 9 0 18 Nov 2018
Inhibited Softmax for Uncertainty Estimation in Neural Networks Marcin Mo.zejko Mateusz Susik Rafal Karczewski UQCV 13 29 0 03 Oct 2018
Probabilistic Logic Programming with Beta-Distributed Random Variables Federico Cerutti Lance M. Kaplan Angelika Kimmig Murat Sensoy 8 12 0 20 Sep 2018
Uncertainty Aware AI ML: Why and How Lance M. Kaplan Federico Cerutti Murat Sensoy Alun D. Preece Paul Sullivan 11 20 0 20 Sep 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015