ReLU activation patterns create polytope decompositions whose dual graph Fiedler partitions correlate with decision boundaries, and cell counts track training loss.
Relu neural networks, polyhedral decompositions, and persistent homology
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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.