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

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Autor(in)
Rieck, Bastian Alexandercc
Togninalli, Matteo
Bock, Christian
Moor, Michael
Horn, Maxcc
Gumbsch, Thomas
Borgwardt, Karsten
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Datum
2019-02-22
Typ
    Conference Paper
Rechte / Lizenz
In Copyright - Non-Commercial Use Permitted
Persistenter Link
https://doi.org/10.3929/ethz-b-000327207
Publikationsstatus
published
Externe Links
https://openreview.net/forum?id=ByxkijC5FQ
Buchtitel
International Conference on Learning Representations (ICLR 2019)
Verlag
OpenReview
Konferenz
7th International Conference on Learning Representations (ICLR 2019), New Orleans, LA, USA, May 6-9, 2019
Thema
Algebraic topology; Persistent homology; Network complexity; Neural network
Organisationseinheit
02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.
09486 - Borgwardt, Karsten M. / Borgwardt, Karsten M.  
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