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cond-mat.dis-nn2026
Lecture notes: From Gaussian processes to feature learning
Moritz Helias, Javed Lindner, Lars Schutzeichel +1
These lecture notes develop the theory of learning in deep and recurrent neuronal networks from the point of view of Bayesian inference. The aim is to enable the reader to understa…
cond-mat.dis-nn2026
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
Jakob Kramp, Javed Lindner, Moritz Helias
Training large neural networks exposes neural scaling laws for the generalization error, which points to a universal behavior across network architectures of learning in high dimen…