3 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang +4
The pairwise interaction paradigm of graph machine learning has predominantly governed the modelling of relational systems. However, graphs alone cannot capture the multi-level int…
cs.LG2020★ 3 cited
Can neural networks learn persistent homology features?
Guido Montúfar, Nina Otter, Yuguang Wang
Topological data analysis uses tools from topology -- the mathematical area that studies shapes -- to create representations of data. In particular, in persistent homology, one stu…
cs.SI2020★ 3 cited
A unified framework for equivalences in social networks
Nina Otter, Mason A. Porter
A key concern in network analysis is the study of social positions and roles of actors in a network. The notion of "position" refers to an equivalence class of nodes that have simi…