Research map / Graph learning / Graph self-supervised learning
Geometry-Guided Generative Representation for Functional Brain Graphs
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation (NeurIPS 2026 · similarity 0.89)
- Biologically Plausible Brain Graph Transformer (ICLR 2025 · similarity 0.88)
- Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold (ICML 2024 · similarity 0.88)
- Platonic Representations in the Human Brain: Unsupervised Recovery of Universal Geometry (NeurIPS 2026 · similarity 0.87)
- DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases (NeurIPS 2025 · similarity 0.86)
- $\textit{NeuroPath}$: A Neural Pathway Transformer for Joining the Dots of Human Connectomes (NeurIPS 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
