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Thomas Gumbsch

1 accepted papers

2019

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

ICLR 2019poster

While many approaches to make neural networks more fathomable have been proposed, they are restricted to interrogating the network with input data. Measures for characterizing and monitoring structural properties, however, have not been developed. In this work, we propose neural persistence, a compl…