الباحثون

Takashi Matsubara

المنشورات 2

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Dirac-Interconnected Neural Elements: Discovering Modularity in Physical Systems Without Reduction

Deep learning has shown remarkable success in the data-driven modeling of dynamical systems. Much of its success is attributed not to the flexibility of neural networks but to inductive biases based on physical prior knowledge, such as energy conservation and symplecticity. However, existing methods do not fully exploi …

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GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling

Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured variability across channels. Conditional flow matching provides a framework for distributional forecasting, yet it remains unclear whether graph-informed source distributions …

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