Jun 13, 2021 · A GNN capable of including symbolic domain knowledge could provide an efficient way of constructing predictive models. Thirdly, to the best of ...

Oct 23, 2020 · The results provide evidence that it is possible to incorporate symbolic domain knowledge into a GNN, and that ILP can play an important role in providing high ...

Taken together, the results provide evidence that it is possible to incorporate symbolic domain knowledge into a GNN, and that ILP can play an important role in ...

Evidence is provided that it is possible to incorporate symbolic domain knowledge into a GNN, and that ILP can play an important role in providing ...

Jan 20, 2022 · This paper examines the inclusion of domain-knowledge by means of changes to: the input, the loss-function, and the architecture of deep networks.

This is to certify that the thesis entitled “Inclusion of Symbolic Domain-Knowledge into Deep Neural Networks” submitted by Tirtharaj Dash, bearing student ID ...

Nov 6, 2024 · Explore how symbolic domain knowledge enhances graph neural networks for improved reasoning and performance in knowledge graphs.

We present a survey of ways in which domain-knowledge has been included when constructing models with neural networks. The inclusion of domain-knowledge is of ...

Our implementations are techniques that combine neural networks and sym- bolic representations, resulting in new neuro-symbolic models, such as: Deep Relational.

Nov 18, 2021 · To the field of graph neural networks, the paper proposes a systematic technique for incorporating symbolic domain-knowledge into GNNs. To the ...