Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications

20 June 2019

Papers citing "Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications"

8 / 8 papers shown

Title
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans J. Orlando Philipp Seeböck Hrvoje Bogunović S. Klimscha C. Grechenig S. Waldstein Bianca S. Gerendas U. Schmidt-Erfurth UQCV 31 56 0 23 Jan 2019
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation T. Nair Doina Precup Douglas L. Arnold Tal Arbel UQCV 58 445 0 03 Aug 2018
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks Guotai Wang Wenqi Li Michael Aertsen Jan Deprest Sebastien Ourselin Tom Vercauteren UQCV MedIm OOD 145 592 0 19 Jul 2018
Deep Reinforcement Learning for Sepsis Treatment Aniruddh Raghu Matthieu Komorowski Imran Ahmed Leo Anthony Celi Peter Szolovits Marzyeh Ghassemi OffRL 57 172 0 27 Nov 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 158 3,454 0 07 Oct 2016
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 187 1,887 0 20 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,271 0 05 Dec 2014