3 papers
cs.LG2026
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…
cs.LG2026
GNNs for Time Series Anomaly Detection: An Open-Source Framework and a Critical Evaluation
Federico Bello, Gonzalo Chiarlone, Marcelo Fiori +2
There is growing interest in applying graph-based methods to Time Series Anomaly Detection (TSAD), particularly Graph Neural Networks (GNNs), as they naturally model dependencies a…
cs.LG2024
LASE: Learned Adjacency Spectral Embeddings
Sofía Pérez Casulo, Marcelo Fiori, Federico Larroca +1
We put forth a principled design of a neural architecture to learn nodal Adjacency Spectral Embeddings (ASE) from graph inputs. By bringing to bear the gradient descent (GD) method…