241 citations · 715 across the 25 of their papers we have counts for
5 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…
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
Artur d'Avila Garcez, Marco Gori, Luis C. Lamb +3
Current advances in Artificial Intelligence and machine learning in general, and deep learning in particular have reached unprecedented impact not only across research communities,…
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…
A Reactive-Darwinian Model for the Ultimatum Game: On the Dominance of Moderation in High Diffusion
Roberto da Silva, Pablo Valverde, Luis C. Lamb
We consider a version of the ultimatum game which simultaneously combines reactive and Darwinian aspects with offers in [0,1]. By reactive aspects, we consider the effects that lea…