40 citations · 43 across the 4 of their papers we have counts for
3 papers · 1 filter
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
Marcio Nicolau, Anderson R. Tavares, Zhiwei Zhang +4
Computational learning theory states that many classes of boolean formulas are learnable in polynomial time. This paper addresses the understudied subject of how, in practice, such…
Superpixel Image Classification with Graph Attention Networks
Pedro H. C. Avelar, Anderson R. Tavares, Thiago L. T. da Silveira +2
This paper presents a methodology for image classification using Graph Neural Network (GNN) models. We transform the input images into region adjacency graphs (RAGs), in which regi…
Discrete and Continuous Deep Residual Learning Over Graphs
Pedro H. C. Avelar, Anderson R. Tavares, Marco Gori +1
In this paper we propose the use of continuous residual modules for graph kernels in Graph Neural Networks. We show how both discrete and continuous residual layers allow for more…