Connectivity Estimation using Stochastic Graph Heat Modelling
A growing number of techniques leverage the spatial structures that underlie many real-world datasets. Despite these advances, the complementary task of estimating spatial structures and understanding their role within these techniques has often been overlooked. In neurophysiological data analysis specifically, numerous methods exist to estimate brain connectivity, but most are not explicitly model-based, dynamic, multivariate, or directed. To address these limitations, we previously introduced noise-driven heat modelling on graphs for neurophysiological connectivity estimation. In this study, we extend this framework by relaxing earlier noise assumptions and adding regularisation to impr...
| Authors | Stephan Goerttler, Min Wu, Fei He |
|---|---|
| Primary category | stat.ML |
| Published | 27 June 2026 |
| Last updated at source | 27 June 2026 |
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