arXiv Machine Learning By Subati Abulikemu, Tiago Azevedo, Michail Mamalakis, John Suckling

Geometry-Guided Generative Representation for Functional Brain Graphs

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arXiv:2511. 04539v2 Announce Type: replace-cross Abstract: In network neuroscience, functional brain systems are often characterized using separate yet related graph-theoretic or spectral descriptors, overlooking how these properties covary and partially overlap across individuals and conditions.

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arXiv AI
Jul 9

Latent graph encoding of multimodal neuroimaging features with generative AI architectures

arXiv:2607. 07027v1 Announce Type: cross Abstract: While generative models enable encoding of complex neuroimaging data for feature generation and reconstruction, developing optimal architectural frameworks with appropriate encoding and latent space processes is crucial for studying structural and functional properties of the brain.

By Ishaan Batta, Meenu Ajith, Vince Calhoun