A general framework for ensemble distribution distillation

A general framework for ensemble distribution distillation

26 February 2020

Jakob Lindqvist

Fredrik Lindsten

Lennart Svensson

Papers citing "A general framework for ensemble distribution distillation"

7 / 7 papers shown

Title
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex Yasushi Esaki Akihiro Nakamura Keisuke Kawano Ryoko Tokuhisa Takuro Kutsuna 46 0 0 21 Feb 2024
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 20 1 0 11 Aug 2023
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification Xue Li Wei Shen Denis Xavier Charles UQCV EDL 54 3 0 12 Sep 2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation Martin Ferianc Miguel R. D. Rodrigues UQCV 49 0 0 19 May 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 66 1,112 0 07 Jul 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 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