A hyperbolic-space framework with geometric entailment constraints and a graph-aware Mamba module improves brain-network classification of ASD and MDD by explicitly modeling ROI-to-community-to-whole-brain hierarchy.
Advances in Neural Information Processing Systems , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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OmniMouse demonstrates data-driven scaling in multi-task brain models on a 150B-token neural dataset, achieving SOTA across prediction, decoding, and forecasting while model size gains saturate.
A generative framework using geometric diffusion for brain networks and tabular diffusion for other organs integrates ICD-coded SDoH proxies to improve disease reasoning on UK Biobank data.
citing papers explorer
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Navigating Hierarchy: Hyperbolic Learning on Brain Graphs for Disorder Diagnosis
A hyperbolic-space framework with geometric entailment constraints and a graph-aware Mamba module improves brain-network classification of ASD and MDD by explicitly modeling ROI-to-community-to-whole-brain hierarchy.
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OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
OmniMouse demonstrates data-driven scaling in multi-task brain models on a 150B-token neural dataset, achieving SOTA across prediction, decoding, and forecasting while model size gains saturate.
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Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning
A generative framework using geometric diffusion for brain networks and tabular diffusion for other organs integrates ICD-coded SDoH proxies to improve disease reasoning on UK Biobank data.