Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment

DOI10.1007/s10994-021-06090-8OpenAlexW3215004982MaRDI QIDQ2127250

Yanyan Li

Publication date: 20 April 2022

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2105.10709

zbMATH Keywords

inductive logic programmingbackground knowledgegraph neural networksmode-directed inverse entailmentneuro-symbolic learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• kLog
• Aleph
• Keras
• PyTorch
• ImageNet
• Adam
• GitHub
• GNMT
• CLEVR dataset
• AlexNet
• WaveNet
• DL2
• CLEVR

Cites Work

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• kLog: a language for logical and relational learning with kernels
• Incorporating symbolic domain knowledge into graph neural networks
• Beyond graph neural networks with lifted relational neural networks
• Inductive Logic Programming: Theory and methods
• 10.1162/153244304773633861
• What Kinds of Relational Features Are Useful for Statistical Learning?
• Representation Learning
• Graph Representation Learning
• Inductive Logic Programming

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