A VAE with SHAP-based interpretability learns low-dimensional codes for Drosophila connectome subgraphs, and the codes can be steered to generate graph subgraphs with targeted edge counts and other properties.
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Unveiling and Steering Connectome Organization with Interpretable Latent Variables
A VAE with SHAP-based interpretability learns low-dimensional codes for Drosophila connectome subgraphs, and the codes can be steered to generate graph subgraphs with targeted edge counts and other properties.