116 citations · 320 across the 21 of their papers we have counts for
4 papers · 1 filter
Assessment of Spatio-Temporal Predictors in the Presence of Missing and Heterogeneous Data
Daniele Zambon, Cesare Alippi
Deep learning methods achieve remarkable predictive performance in modeling complex, large-scale data. However, assessing the quality of derived models has become increasingly chal…
AZ-whiteness test: a test for uncorrelated noise on spatio-temporal graphs
Daniele Zambon, Cesare Alippi
We present the first whiteness test for graphs, i.e., a whiteness test for multivariate time series associated with the nodes of a dynamic graph. The statistical test aims at findi…
Change Point Methods on a Sequence of Graphs
Daniele Zambon, Cesare Alippi, Lorenzo Livi
Given a finite sequence of graphs, e.g., coming from technological, biological, and social networks, the paper proposes a methodology to identify possible changes in stationarity i…
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds
Daniele Grattarola, Daniele Zambon, Cesare Alippi +1
The space of graphs is often characterised by a non-trivial geometry, which complicates learning and inference in practical applications. A common approach is to use embedding tech…