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MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator

MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator

2 September 2021
Rhys Green
Matthew Rowe
A. Polleri
ArXivPDFHTML

Papers citing "MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator"

4 / 4 papers shown
Title
Combining pre-trained Vision Transformers and CIDER for Out Of Domain
  Detection
Combining pre-trained Vision Transformers and CIDER for Out Of Domain Detection
Grégor Jouet
Clément Duhart
Francis Rousseaux
Julio Laborde
Cyril de Runz
ViT
33
0
0
06 Sep 2023
Insurance pricing on price comparison websites via reinforcement
  learning
Insurance pricing on price comparison websites via reinforcement learning
Tanut Treetanthiploet
Yufei Zhang
Lukasz Szpruch
Isaac Bowers-Barnard
Henrietta Ridley
James Hickey
C. Pearce
OffRL
24
2
0
14 Aug 2023
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
1