Molecule Property Prediction

[aishikaranjan]

Description

The model uses Graph Neural Networks (GNNs) to predict molecular properties based on the molecular structure. It incorporates GINEConv and GATv2Conv layers to effectively learn from atomic and bond features, enabling accurate predictions for various chemical datasets. This architecture enables the model to make accurate predictions on chemical datasets, aiding in drug discovery and chemical analysis. By embedding both atom and bond information, the model effectively generalizes across different molecular structures, demonstrating high performance on both validation and test sets.

Fixes #626

Type of change

• Added a new machine learning frameworks, libraries or software.
• Documentation update

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings

[github-actions]

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