arXiv Machine Learning
High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching
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TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching
arXiv:2607. 16894v1 Announce Type: new Abstract: Many complex systems such as brain networks, financial markets, and gene-regulatory circuits are described not by a fixed graph but by one that changes over time.
arXiv Machine Learning
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Connectome-to-Function: Conditional Generative Latent Representations for Reservoir Computing
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Geometry-Guided Generative Representation for Functional Brain Graphs
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arXiv Machine Learning
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Reservoir-Based Graph Convolutional Networks
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arXiv Machine Learning
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GraM-Diff: A Unified Graph-Mamba Diffusion Framework for EEG-Based Alzheimer's Disease Data Generation and Diagnosis
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arXiv Machine Learning
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Variational autoencoders with latent high-dimensional steady geometric flows for dynamics
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