Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural
Networks

v1v2v3 (latest)

Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks

23 August 2019

Roberto Paredes Palacios

D. Ramos-Castro

ArXiv (abs)PDF HTML

Papers citing "Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks"

7 / 7 papers shown

Title
Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks Sérgio A. Balanya Juan Maroñas Daniel Ramos OOD 83 15 0 31 Jul 2022
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability Qiyiwen Zhang Zhiqi Bu Kan Chen Qi Long BDL UQCV 65 11 0 18 Jul 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 355 1,945 0 12 Nov 2020
Transforming Gaussian Processes With Normalizing Flows Juan Maroñas Oliver Hamelijnck Jeremias Knoblauch Theodoros Damoulas 105 34 0 03 Nov 2020
Local Temperature Scaling for Probability Calibration Zhipeng Ding Xu Han Peirong Liu Marc Niethammer 119 81 0 12 Aug 2020
Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks Davood Karimi Ali Gholipour OOD 61 9 0 12 Apr 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 86 6 0 22 Mar 2020