8 citations · 18 across the 9 of their papers we have counts for
10 papers
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…
Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset
Ignacio Boero, Santiago Diaz, Tomás Vázquez +3
The Optimal Reactive Power Dispatch (ORPD) problem plays a crucial role in power system operations, ensuring voltage stability and minimizing power losses. Recent advances in machi…
Weighted Random Dot Product Graphs
Bernardo Marenco, Paola Bermolen, Marcelo Fiori +2
Modeling of intricate relational patterns has become a cornerstone of contemporary statistical research and related data science fields. Networks, represented as graphs, offer a na…
Graph Contrastive Learning for Connectome Classification
Martín Schmidt, Sara Silva, Federico Larroca +2
With recent advancements in non-invasive techniques for measuring brain activity, such as magnetic resonance imaging (MRI), the study of structural and functional brain networks th…
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…
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…
Sequential Algorithms and Independent Sets Discovering on Large Sparse Random Graphs
Paola Bermolen, Matthieu Jonckheere, Federico Larroca +1
Computing the size of maximum independent sets is a NP-hard problem for fixed graphs. Characterizing and designing efficient algorithms to estimate this independence number for ran…
Museum Accessibility Through Wi-Fi Indoor Positioning
Antonio Bracco, Federico Grunwald, Agustin Navcevich +2
Accessibility has long been a primary concern for major museums around the world. This is no exception for the Museo Nacional de Artes Visuales (MNAV, National Museum of Visual Art…
Estimating the Spatial Reuse with Configuration Models
Paola Bermolen, Matthieu Jonckheere, Federico Larroca +1
We propose a new methodology to estimate the spatial reuse of CSMA-like scheduling. Instead of focusing on spatial configurations of users, we model the interferences between users…