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Deep Active Learning by Model Interpretability

Deep Active Learning by Model Interpretability

23 July 2020
Qiang Liu
Zhaocheng Liu
Xiaofang Zhu
Yeliang Xiu
ArXivPDFHTML

Papers citing "Deep Active Learning by Model Interpretability"

4 / 4 papers shown
Title
ProtoAL: Interpretable Deep Active Learning with prototypes for medical
  imaging
ProtoAL: Interpretable Deep Active Learning with prototypes for medical imaging
Iury B. de A. Santos
André C.P.L.F. de Carvalho
MedIm
30
1
0
06 Apr 2024
Active Learning for Graph Neural Networks via Node Feature Propagation
Active Learning for Graph Neural Networks via Node Feature Propagation
Yuexin Wu
Yichong Xu
Aarti Singh
Yiming Yang
A. Dubrawski
GNN
AI4CE
46
63
0
16 Oct 2019
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
285
9,138
0
06 Jun 2015
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
255
13,364
0
25 Aug 2014
1