2 citations · 2 across the 2 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2020
Simplicial Neural Networks
Stefania Ebli, Michaël Defferrard, Gard Spreemann
We present simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes. These are na…
cs.LG2019
A Notion of Harmonic Clustering in Simplicial Complexes
Stefania Ebli, Gard Spreemann
We outline a novel clustering scheme for simplicial complexes that produces clusters of simplices in a way that is sensitive to the homology of the complex. The method is inspired…
cs.LG2019
Topology of Learning in Artificial Neural Networks
Maxime Gabella
Understanding how neural networks learn remains one of the central challenges in machine learning research. From random at the start of training, the weights of a neural network ev…