119 citations · 157 across the 13 of their papers we have counts for
3 papers · 1 filter
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…
Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems
Henrique Lemos, Marcelo Prates, Pedro Avelar +1
Deep learning has consistently defied state-of-the-art techniques in many fields over the last decade. However, we are just beginning to understand the capabilities of neural learn…
Typed Graph Networks
Marcelo O. R. Prates, Pedro H. C. Avelar, Henrique Lemos +2
Recently, the deep learning community has given growing attention to neural architectures engineered to learn problems in relational domains. Convolutional Neural Networks employ p…