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Learn to Propagate Reliably on Noisy Affinity Graphs

Learn to Propagate Reliably on Noisy Affinity Graphs

17 July 2020
Lei Yang
Qingqiu Huang
Huaiyi Huang
Linning Xu
Dahua Lin
    GNN
ArXivPDFHTML

Papers citing "Learn to Propagate Reliably on Noisy Affinity Graphs"

4 / 4 papers shown
Title
From Trailers to Storylines: An Efficient Way to Learn from Movies
From Trailers to Storylines: An Efficient Way to Learn from Movies
Qingqiu Huang
Yuanjun Xiong
Yu Xiong
Yuqi Zhang
Dahua Lin
28
26
0
14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
244
1,276
0
06 Mar 2017
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
268
5,652
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
247
9,109
0
06 Jun 2015
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