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Interpretable Graph-Based Semi-Supervised Learning via Flows

Interpretable Graph-Based Semi-Supervised Learning via Flows

14 September 2017
Raif M. Rustamov
James T. Klosowski
ArXiv (abs)PDFHTML

Papers citing "Interpretable Graph-Based Semi-Supervised Learning via Flows"

4 / 4 papers shown
SFi-Former: Sparse Flow Induced Attention for Graph Transformer
SFi-Former: Sparse Flow Induced Attention for Graph TransformerInternational Conference on Multimedia Retrieval (ICMR), 2025
Hao Sun
J. Q. Shi
Xinming Zhang
Miao Zhang
B. Li
327
0
0
29 Apr 2025
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic
  Review on Evaluating Explainable AI
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIACM Computing Surveys (ACM CSUR), 2022
Meike Nauta
Jan Trienes
Shreyasi Pathak
Elisa Nguyen
Michelle Peters
Yasmin Schmitt
Jorg Schlotterer
M. V. Keulen
C. Seifert
ELMXAI
812
640
0
20 Jan 2022
An interpretable semi-supervised classifier using two different
  strategies for amended self-labeling
An interpretable semi-supervised classifier using two different strategies for amended self-labeling
Isel Grau
Dipankar Sengupta
M. Lorenzo
A. Nowé
SSL
294
4
0
26 Jan 2020
Training Machine Learning Models by Regularizing their Explanations
Training Machine Learning Models by Regularizing their Explanations
A. Ross
FaML
142
0
0
29 Sep 2018
1
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