Hugging Face Trending Papers
GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling
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arXiv AI
4d ago
GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling
arXiv:2609.37934v1 Announce Type: new Abstract: Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured varia...
arXiv Machine Learning
Jul 21
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 Statistics ML
Sep 15
Assumption-Lean Inference for Spectral Differential Network Analysis of High-Dimensional Time Series
arXiv:2609.13609v1 Announce Type: cross Abstract: Network analysis for multivariate time series is popular in many fields, from neuroscience to seismology. The inverse spectral density is a common ch...
arXiv Machine Learning
Jul 23
Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics
arXiv:2607. 19429v1 Announce Type: new Abstract: Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational approaches reduce these dynamics to static features.
Hugging Face Trending Papers
Jul 8
Stability of Flow Models for Graph Signals
Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While favorable stability properties of Graph Neural Networks (GNNs) have been well documented, it is unclear how structural errors propagate through the dynamics of continuous generative flow models that are gaining traction for graph signal generation.
arXiv Machine Learning
Jun 11
SpaTeoGL: Spatiotemporal Graph Learning for Interpretable Seizure Onset Zone Analysis from Intracranial EEG
arXiv:2602. 11801v2 Announce Type: replace Abstract: Accurate localization of the seizure onset zone (SOZ) from intracranial EEG (iEEG) is essential for epilepsy surgery but is challenged by complex spatiotemporal seizure dynamics.