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Evidential Deep Learning to Quantify Classification Uncertainty

5 June 2018

Papers citing "Evidential Deep Learning to Quantify Classification Uncertainty"

50 / 574 papers shown

Title
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping Raphael van Kempen Bastian Lampe Timo Woopen L. Eckstein 189 13 0 25 Feb 2021
Handling Epistemic and Aleatory Uncertainties in Probabilistic CircuitsMachine-mediated learning (ML), 2021 Federico Cerutti Lance M. Kaplan Angelika Kimmig Murat Sensoy TPM 125 16 0 22 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 601 109 0 16 Feb 2021
Trusted Multi-View ClassificationInternational Conference on Learning Representations (ICLR), 2021 Zongbo Han Changqing Zhang Huazhu Fu Qiufeng Wang EDL 196 210 0 03 Feb 2021
Probabilistic Trust Intervals for Out of Distribution Detection Gagandeep Singh Deepak Mishra UQCV AAML OOD 99 0 0 02 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage AnalysisIEEE Transactions on Software Engineering (TSE), 2021 Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 272 21 0 28 Jan 2021
Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma Chao Li Wenjian Huang Xi Chen Yiran Wei S. Price Carola-Bibiane Schönlieb MedIm 264 1 0 21 Jan 2021
Multidimensional Uncertainty-Aware Evidential Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2020 Yibo Hu Yuzhe Ou Xujiang Zhao Jin-Hee Cho Feng Chen EDL UQCV AAML 231 30 0 26 Dec 2020
Post-hoc Uncertainty Calibration for Domain Drift ScenariosComputer Vision and Pattern Recognition (CVPR), 2020 Christian Tomani Sebastian Gruber Muhammed Ebrar Erdem Zorah Lähner Florian Buettner UQCV 338 77 0 20 Dec 2020
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial CalibrationAAAI Conference on Artificial Intelligence (AAAI), 2019 Christian Tomani Florian Buettner UQCV AAML OOD 283 41 0 20 Dec 2020
Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning Christina Petschnigg Juergen Pilz UQCV 3DPC 119 9 0 13 Dec 2020
NSL: Hybrid Interpretable Learning From Noisy Raw Data Daniel Cunnington A. Russo Mark Law Jorge Lobo Lance M. Kaplan NAI 223 5 0 09 Dec 2020
Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions Jun Wang Shaoguo Wen Kaixing Chen Jianghua Yu Xiaoxia Zhou Peng Gao Changsheng Li Guotong Xie ISeg 97 19 0 09 Dec 2020
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantificationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch BDL UQCV 311 32 0 04 Dec 2020
Extended T: Learning with Mixed Closed-set and Open-set Noisy LabelsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Jiankang Deng Jiatong Li Yinian Mao NoLa 152 11 0 02 Dec 2020
Learning a metacognition for object perception Marlene D. Berke M. Belledonne J. Jara-Ettinger OCL LRM 118 1 0 30 Nov 2020
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving Di Feng Ali Harakeh Steven Waslander Klaus C. J. Dietmayer AAML UQCV EDL 316 282 0 20 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and ChallengesInformation Fusion (Inf. Fusion), 2020 Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Tianpeng Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 931 2,266 0 12 Nov 2020
EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels Ragav Sachdeva F. Cordeiro Vasileios Belagiannis Ian Reid G. Carneiro NoLa 151 45 0 11 Nov 2020
APPLI: Adaptive Planner Parameter Learning From InterventionsIEEE International Conference on Robotics and Automation (ICRA), 2020 Zizhao Wang Xuesu Xiao Bo Liu Garrett A. Warnell Peter Stone 322 60 0 01 Nov 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?International Conference on Machine Learning (ICML), 2020 Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 311 53 0 28 Oct 2020
Uncertainty Aware Semi-Supervised Learning on Graph DataNeural Information Processing Systems (NeurIPS), 2020 Xujiang Zhao Feng Chen Shu Hu Jin-Hee Cho UQCV EDL BDL 490 159 0 24 Oct 2020
Towards human-agent knowledge fusion (HAKF) in support of distributed coalition teams Dave Braines Federico Cerutti Marc Roig Vilamala Mani B. Srivastava Alun D. Preece G. Pearson 100 4 0 23 Oct 2020
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution ExamplesNeural Information Processing Systems (NeurIPS), 2020 Jay Nandy Wynne Hsu Yang Deng UQCV 227 70 0 20 Oct 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet NetworksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 Theodoros Tsiligkaridis UQCV 93 8 0 19 Oct 2020
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersNeural Information Processing Systems (NeurIPS), 2020 Masha Itkina Boris Ivanovic Ransalu Senanayake Mykel J. Kochenderfer Marco Pavone 214 18 0 19 Oct 2020
Multi-Loss Sub-Ensembles for Accurate Classification with Uncertainty Estimation Omer Achrack Raizy Kellerman Ouriel Barzilay UQCV BDL 189 10 0 05 Oct 2020
Uncertainty Sets for Image Classifiers using Conformal Prediction Anastasios Nikolas Angelopoulos Stephen Bates Jitendra Malik Sai Li UQCV 626 414 0 29 Sep 2020
Using Subjective Logic to Estimate Uncertainty in Multi-Armed Bandit Problems Fabio Massimo Zennaro A. Jøsang 105 4 0 17 Aug 2020
Maximizing BCI Human Feedback using Active LearningIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2020 Zizhao Wang Junyao Shi Iretiayo Akinola Peter K. Allen 85 12 0 11 Aug 2020
$Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertainty$ Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertainty Amelia Jiménez-Sánchez Diana Mateus S. Kirchhoff C. Kirchhoff P. Biberthaler Nassir Navab M. A. G. Ballester Gemma Piella 120 22 0 31 Jul 2020
DEAL: Deep Evidential Active Learning for Image Classification Patrick Hemmer Niklas Kühl Jakob Schöffer 196 43 0 22 Jul 2020
Unsupervised Domain Adaptation in the Absence of Source Data Roshni Sahoo Divya Shanmugam John Guttag OOD 179 19 0 20 Jul 2020
Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment Florin-Cristian Ghesu Bogdan Georgescu Awais Mansoor Y. Yoo Eli Gibson ... Ramandeep Singh S. Digumarthy Mannudeep K. Kalra Sasa Grbic Dorin Comaniciu UQCV EDL 120 64 0 08 Jul 2020
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain Takahiro Mimori Keiko Sasada H. Matsui Issei Sato UQCV 342 9 0 03 Jul 2020
Regression Prior Networks A. Malinin Sergey Chervontsev Ivan Provilkov Mark Gales BDL UQCV 242 39 0 20 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 787 517 0 17 Jun 2020
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes Manuel Haussmann S. Gerwinn Andreas Look Barbara Rakitsch M. Kandemir 294 18 0 17 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 382 211 0 16 Jun 2020
Mean-Field Approximation to Gaussian-Softmax Integral with Application to Uncertainty Estimation Zhiyun Lu Eugene Ie Fei Sha UQCV BDL 196 16 0 13 Jun 2020
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric UncertaintyNeural Information Processing Systems (NeurIPS), 2020 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 147 128 0 10 Jun 2020
Uncertainty-Aware Deep Classifiers using Generative Models Murat Sensoy Lance M. Kaplan Federico Cerutti Maryam Saleki UQCV OOD 231 85 0 07 Jun 2020
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis P. Poduval H. Loya A. Sethi BDL UQCV 127 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 284 40 0 22 Apr 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial AttacksIEEE Transactions on Medical Imaging (TMI), 2020 Siqi Liu A. Setio Florin-Cristian Ghesu Eli Gibson Sasa Grbic Bogdan Georgescu Dorin Comaniciu AAML OOD 302 44 0 08 Mar 2020
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning Yiming Sun Bing Cao Q. Hu Q. Hu 411 429 0 05 Mar 2020
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context DiscoveryInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Zepeng Huo Arash Pakbin Xiaohan Chen N. Hurley Ye Yuan Xiaoning Qian Zinan Lin Shuai Huang B. Mortazavi HAI 150 14 0 03 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep NetworksConference on Uncertainty in Artificial Intelligence (UAI), 2020 Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 418 39 0 02 Mar 2020
Adversarial Ranking Attack and DefenseEuropean Conference on Computer Vision (ECCV), 2020 Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 291 42 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksInternational Conference on Machine Learning (ICML), 2020 Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 347 326 0 24 Feb 2020