8 citations · 8 across the 4 of their papers we have counts for
4 papers · 1 filter
Hyperbolic Graph Representation Learning: Embed in One Metric, Optimize with Another
Federico Larroca, Paola Bermolen, Marcelo Fiori +1
Hierarchical graphs embed in hyperbolic space with lower distortion than in Euclidean space owing to its negative curvature. However, their gradient-based learning is hampered at l…
A Unified Framework of Hyperbolic Graph Representation Learning Methods
Sofía Pérez Casulo, Marcelo Fiori, Bernardo Marenco +1
Hyperbolic geometry has emerged as an effective latent space for representing complex networks, owing to its ability to capture hierarchical organization and heterogeneous connecti…
Gradient-Based Spectral Embeddings of Random Dot Product Graphs
Marcelo Fiori, Bernardo Marenco, Federico Larroca +2
The Random Dot Product Graph (RDPG) is a generative model for relational data, where nodes are represented via latent vectors in low-dimensional Euclidean space. RDPGs crucially po…
Online Change Point Detection for Weighted and Directed Random Dot Product Graphs
Bernardo Marenco, Paola Bermolen, Marcelo Fiori +2
Given a sequence of random (directed and weighted) graphs, we address the problem of online monitoring and detection of changes in the underlying data distribution. Our idea is to…