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Improving Confidence Estimates for Unfamiliar Examples
v1v2v3v4v5v6 (latest)

Improving Confidence Estimates for Unfamiliar Examples

9 April 2018
Zhizhong Li
Derek Hoiem
ArXiv (abs)PDFHTMLGithub (12★)

Papers citing "Improving Confidence Estimates for Unfamiliar Examples"

6 / 6 papers shown
Self-Knowledge Distillation via Dropout
Self-Knowledge Distillation via DropoutComputer Vision and Image Understanding (CVIU), 2022
Hyoje Lee
Yeachan Park
Hyun Seo
Myung-joo Kang
FedML
260
27
0
11 Aug 2022
Ensemble Distillation for Structured Prediction: Calibrated, Accurate,
  Fast-Choose Three
Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three
Steven Reich
David Mueller
Nicholas Andrews
BDLOODUQCV
220
13
0
13 Oct 2020
Angular Visual Hardness
Angular Visual HardnessInternational Conference on Machine Learning (ICML), 2019
Beidi Chen
Weiyang Liu
Zhiding Yu
Jan Kautz
Anshumali Shrivastava
Animesh Garg
Anima Anandkumar
AAML
346
57
0
04 Dec 2019
Efficient Evaluation-Time Uncertainty Estimation by Improved
  Distillation
Efficient Evaluation-Time Uncertainty Estimation by Improved DistillationInternational Conference on Machine Learning (ICML), 2019
Erik Englesson
Hossein Azizpour
UQCV
245
8
0
12 Jun 2019
Ensemble Distribution Distillation
Ensemble Distribution DistillationInternational Conference on Learning Representations (ICLR), 2019
A. Malinin
Bruno Mlodozeniec
Mark Gales
UQCV
689
271
0
30 Apr 2019
OMNIA Faster R-CNN: Detection in the wild through dataset merging and
  soft distillation
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation
Alexandre Ramé
Emilien Garreau
H. Ben-younes
Charles Ollion
ObjD
243
18
0
06 Dec 2018
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