3.1k citations · 16.1k across the 160 of their papers we have counts for
162 papers
Learning from data with structured missingness
Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti +17
Missing data are an unavoidable complication in many machine learning tasks. When data are `missing at random' there exist a range of tools and techniques to deal with the issue. H…
Persistent Dirac for molecular representation
JunJie Wee, Ginestra Bianconi, Kelin Xia
Molecular representations are of fundamental importance for the modeling and analysis of molecular systems. Representation models and in general approaches based on topological dat…
Dirac signal processing of higher-order topological signals
Lucille Calmon, Michael T. Schaub, Ginestra Bianconi
Higher-order networks can sustain topological signals which are variables associated not only to the nodes, but also to the links, to the triangles and in general to the higher dim…
Higher-order signal processing with the Dirac operator
Lucille Calmon, Michael T. Schaub, Ginestra Bianconi
The processing of signals on simplicial and cellular complexes defined by nodes, edges, and higher-order cells has recently emerged as a principled extension of graph signal proces…
Dirac gauge theory for topological spinors in 3+1 dimensional networks
Ginestra Bianconi
Gauge theories on graphs and networks are attracting increasing attention not only as approaches to quantum gravity but also as models for performing quantum computation. Here we p…
Local Dirac Synchronization on Networks
Lucille Calmon, Sanjukta Krishnagopal, Ginestra Bianconi
We propose Local Dirac Synchronization which uses the Dirac operator to capture the dynamics of coupled nodes and link signals on an arbitrary network. In Local Dirac Synchronizati…