AI RESEARCH
State-Space NTK Collapse Near Bifurcations
arXiv CS.LG
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ArXi:2605.12763v1 Announce Type: new Rich feature learning in tasks that unfold over time often requires the model to pass through bifurcations, constituting qualitative changes in the underlying model dynamics. We develop a local theory of gradient descent near these transitions through the empirical state-space neural tangent kernel (s