ReLU activation patterns create polytope decompositions whose dual graph Fiedler partitions correlate with decision boundaries, and cell counts track training loss.
A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019
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Topological Signatures of ReLU Neural Network Activation Patterns
ReLU activation patterns create polytope decompositions whose dual graph Fiedler partitions correlate with decision boundaries, and cell counts track training loss.