ReLU activation patterns create polytope decompositions whose dual graph Fiedler partitions correlate with decision boundaries, and cell counts track training loss.
On the expressive power of deep neural networks.International conference on machine learning, pages 2847–2854
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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.