Workflow Example: Visualize the Generated Space¶
This workflow focuses on understanding the generated molecule set as a distribution rather than only as individual samples. After generation, molecules are featurized and projected into a lower-dimensional representation for interpretation.
Conceptual Flow¶
[Generated 3D molecules]
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v
[Featurize]
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v
[Project to low-dimensional space]
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v
[Visualize clusters, spread, and outliers]
What Visualization Helps You See¶
Visualization helps answer questions that summary metrics cannot show clearly:
Is the generated set concentrated or broadly distributed?
Are there distinct structural clusters?
Do generated molecules overlap with or extend beyond the reference set?
This is especially useful when comparing:
a base model versus a transfer-learned model,
unconditional versus guided generation,
different filtering or ranking strategies.
Common Projection Ideas¶
The draft mentions feature representations such as SOAP or learned embeddings, followed by low-dimensional projections such as UMAP or t-SNE. The exact representation is less important than the goal: building an interpretable picture of the generated chemical space.