Emergence of Fibrations, Compression, and Symmetry Breaking in Artificial Neural Networks
Artificial neural networks are often regarded as powerful yet opaque black boxes. Here, we demonstrate that learning in deep neural networks generates local symmetries known in graph theory as fibrations and coverings. We prove that covering symmetries are stable attractors of stochastic gradient descent. Consistent wi...
O. Velarde, Lucas C. Parra, Alireza Hashemi et al.
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