dynamical mean field theory
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Machine learning generalization linked to superconducting transition physics
Researchers have utilized dynamical mean field theory to explain the phenomenon of "double descent" in machine learning, where generalization improves even when model capacity exceeds data points. This behavior is ident…
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Dynamical Mean Field Theory Explains AI Feature Learning
Pierfrancesco Urbani presented research on applying dynamical mean field theory to analyze feature learning and overfitting in large neural networks. The talk, held at the Harvard Center of Mathematical Sciences and App…
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New theories explore spectral dynamics in deep neural network training
Two new arXiv papers explore the spectral dynamics of deep neural networks during training. One paper introduces "Neural Low-Degree Filtering" (Neural LoFi) as a theoretical framework to understand hierarchical feature …