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MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation

MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation

21 May 2024
Zhaoning Yu
Hongyang Gao
ArXivPDFHTML

Papers citing "MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation"

6 / 6 papers shown
Title
Explaining the Explainers in Graph Neural Networks: a Comparative Study
Explaining the Explainers in Graph Neural Networks: a Comparative Study
Antonio Longa
Steve Azzolin
G. Santin
G. Cencetti
Pietro Lio'
Bruno Lepri
Andrea Passerini
34
27
0
27 Oct 2022
polyBERT: A chemical language model to enable fully machine-driven
  ultrafast polymer informatics
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics
Christopher Kuenneth
R. Ramprasad
18
99
0
29 Sep 2022
Graph Neural Networks for Molecules
Graph Neural Networks for Molecules
Yuyang Wang
Zijie Li
A. Farimani
GNN
AI4CE
38
20
0
12 Sep 2022
Molecular Representation Learning via Heterogeneous Motif Graph Neural
  Networks
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks
Zhaoning Yu
Hongyang Gao
21
38
0
01 Feb 2022
MotifExplainer: a Motif-based Graph Neural Network Explainer
MotifExplainer: a Motif-based Graph Neural Network Explainer
Zhaoning Yu
Hongyang Gao
24
14
0
01 Feb 2022
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
208
1,205
0
12 Feb 2018
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