3 papers
cs.LG2026
Attention Graphons: A Graph Limit Perspective on Graph Transformers
Caio F. Deberaldini Netto, Moshe Eliasof, Luana Ruiz
Graph Transformers produce, for each attention head, a dense matrix of learned pairwise interactions. We ask a fundamental question: do these attention-induced graphs c…
cs.LG2025
Graph Semi-Supervised Learning for Point Classification on Data Manifolds
Caio F. Deberaldini Netto, Zhiyang Wang, Luana Ruiz
We propose a graph semi-supervised learning framework for classification tasks on data manifolds. Motivated by the manifold hypothesis, we model data as points sampled from a low-d…
cs.LG2024
Improved Image Classification with Manifold Neural Networks
Caio F. Deberaldini Netto, Zhiyang Wang, Luana Ruiz
Graph Neural Networks (GNNs) have gained popularity in various learning tasks, with successful applications in fields like molecular biology, transportation systems, and electrical…