graph-network-explainability

graph-network-explainability

baldassarreFe

Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)

bioinformatics artificial-intelligence
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127 Stars
16 Forks
127 Watchers
Jupyter Notebook Language
100 SrcLog Score
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$39.8K
Market Value
$68.4K
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11 data points  ·  2021-08-01 → 2026-04-01
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What is the baldassarreFe/graph-network-explainability GitHub project? Description: "Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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