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Deep Learning as Ricci Flow
April 23, 2024, 4:42 a.m. | Anthony Baptista, Alessandro Barp, Tapabrata Chakraborti, Chris Harbron, Ben D. MacArthur, Christopher R. S. Banerji
cs.LG updates on arXiv.org arxiv.org
Abstract: Deep neural networks (DNNs) are powerful tools for approximating the distribution of complex data. It is known that data passing through a trained DNN classifier undergoes a series of geometric and topological simplifications. While some progress has been made toward understanding these transformations in neural networks with smooth activation functions, an understanding in the more general setting of non-smooth activation functions, such as the rectified linear unit (ReLU), which tend to perform better, is required. …
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