119 citations · 148 across the 11 of their papers we have counts for
5 papers · 1 filter
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases
Henrique Lemos, Pedro Avelar, Marcelo Prates +2
The recent developments and growing interest in neural-symbolic models has shown that hybrid approaches can offer richer models for Artificial Intelligence. The integration of effe…
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…
Neural Networks Models for Analyzing Magic: the Gathering Cards
Felipe Zilio, Marcelo Prates, Luis Lamb
Historically, games of all kinds have often been the subject of study in scientific works of Computer Science, including the field of machine learning. By using machine learning te…
Learning to Solve NP-Complete Problems - A Graph Neural Network for Decision TSP
Marcelo O. R. Prates, Pedro H. C. Avelar, Henrique Lemos +2
Graph Neural Networks (GNN) are a promising technique for bridging differential programming and combinatorial domains. GNNs employ trainable modules which can be assembled in diffe…