PrototypeCommon
baldassarreFe/graph-network-explainability
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)
- Owner
- baldassarreFe (personal account)
- Stars
- Stars: 127
- Forks
- Forks: 16
- Language
- Jupyter Notebook
- License
- None
- Created
- 2019
- Topics
- graph-networksexplainabilitybioinformaticsartificial-intelligence
- Tier
- Prototype (100 to 249 ★) What this tier means
More repos by baldassarreFe
All 2 repos by baldassarreFe- baldassarreFe/deep-koalarizationStars: 414PythonAlpha
Nearby in Jupyter Notebook
All Jupyter Notebook repos- anandchauhan21/Desing_of_Data_StructuresStars: 127Jupyter NotebookPrototype
- nileshhadalgi016/Awesome-ML-AI-TutorialStars: 127Jupyter NotebookPrototype
- Quackone/homr_guiStars: 127Jupyter NotebookPrototype
- dfinke/PowerShellHumanizerStars: 127Jupyter NotebookPrototype
- ipeirotis/dealing_with_dataStars: 127Jupyter NotebookPrototype
- dtamayo/reboundxStars: 127Jupyter NotebookPrototype