Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms

22 April 2020

Papers citing "Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms"

22 / 22 papers shown

Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 205 0 0 04 May 2025
Geometry-Informed Neural Operator Transformer Qibang Liu Vincient Zhong Hadi Meidani Diab Abueidda S. Koric Philippe Geubelle AI4CE 46 1 0 28 Apr 2025
Legitimate ground-truth-free metrics for deep uncertainty classification scoring Arthur Pignet Chiara Regniez John Klein 72 1 0 30 Oct 2024
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation S. Chatterjee Franziska Gaidzik Alessandro Sciarra Hendrik Mattern G. Janiga Oliver Speck Andreas Nürnberger S. Pathiraja 52 0 0 25 Dec 2023
Quantification of Uncertainty with Adversarial Models Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi Günter Klambauer Sepp Hochreiter UQCV 47 14 0 06 Jul 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 38 75 0 07 May 2023
Fairness Uncertainty Quantification: How certain are you that the model is fair? Abhishek Roy P. Mohapatra 34 5 0 27 Apr 2023
Applications of AI in Astronomy S. Djorgovski Ashish Mahabal Matthew Graham K. Polsterer A. Krone-Martins 26 2 0 03 Dec 2022
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions Joseph B. Choi Phong C. H. Nguyen O. Sen H. Udaykumar Stephen Seung-Yeob Baek PINN AI4CE 29 11 0 15 Nov 2022
A view on model misspecification in uncertainty quantification Yuko Kato David Tax Marco Loog 30 3 0 30 Oct 2022
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 43 2 0 12 Jun 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A. Maraval Matthieu Zimmer Antoine Grosnit Rasul Tutunov Jun Wang H. Ammar 35 2 0 27 May 2022
Self-Normalized Density Map (SNDM) for Counting Microbiological Objects K. Graczyk J. Pawlowski Sylwia Majchrowska Tomasz Golan 28 9 0 15 Mar 2022
Machine Learning and Cosmology C. Dvorkin S. Mishra-Sharma Brian D. Nord V. A. Villar Camille Avestruz ... A. Ćiprijanović Andrew J. Connolly L. Garrison G. Narayan F. Villaescusa-Navarro AI4CE 34 12 0 15 Mar 2022
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 40 8 0 10 Sep 2021
The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data Natália Villa Nova Rodrigues L. Abramo Nina Sumiko Tomita Hirata 24 6 0 10 Aug 2021
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements L. Hoffmann I. Fortmeier Clemens Elster UQCV 25 28 0 01 Mar 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 42 2 0 04 Jan 2021
DeepShadows: Separating Low Surface Brightness Galaxies from Artifacts using Deep Learning Dimitrios Tanoglidis A. Ćiprijanović A. Drlica-Wagner 18 15 0 24 Nov 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 278 5,695 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,640 0 03 Jul 2012