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Lifted Relational Neural Networks


Learning Predictive Categories Using Lifted Relational Neural ...

Lifted relational neural networks (LRNNs) are a flexible neural-symbolic framework based on the idea of lifted modelling.

Lifted Relational Neural Networks: Efficient Learning of Latent ...

We propose a method to combine the interpretability and expressive power of firstorder logic with the effectiveness of neural network learning.

Beyond Graph Neural Networks with Lifted Relational ... - Underline

On-demand video platform giving you access to lectures from conferences worldwide.

A review of some techniques for inclusion of domain-knowledge into ...

Beyond graph neural networks with lifted relational neural networks. arXiv preprint arXiv:2007.06286 (2020). Sourek, G., Aschenbrenner, V ...

Lifted Relational Neural Networks - Talks - University of Cambridge

Lifted Relational Neural Networks (LRNNs) were introduced as a framework for combining logic programming with neural networks for efficient ...

Selected Publications - Gustav Šír

Stacked Structure Learning for Lifted Relational Neural Networks. Published in International Conference on Inductive Logic Programming, 2017. A structure ...

GustikS/NeuraLogic: Deep relational learning through ... - GitHub

For detailed syntax and semantics, please check out the concept of "Lifted Relational Neural Networks". For a deep dive into the principles in full scientific ...

Ondrej Kuzelka - DBLP

Beyond graph neural networks with lifted relational neural networks. Mach. Learn. 110(7): 1695-1738 (2021). [c50]. view. electronic edition ...

KR 2023

LOGICNEURAL directed StarAI approach and logic programs. Logic as a neural program. Lifted Relational Neural Networks. • Directed (fuzzy) NeSy. • similar in ...

Deep Learning with Relational Logic Representations - IOS Press

... relational learning framework called Lifted Relational Neural Networks, which generalizes the standard deep learning models into the ...

Papers with Code - Martin Svatos

Lifted Relational Neural Networks (LRNNs) describe relational domains using weighted first-order rules which act as templates for constructing feed-forward ...

RelNN: A Deep Neural Model for Relational Learning - AAAI

Lifted relational neural networks. In Proceedings of the 2015th International Conference on Cognitive Computa- tion: Integrating Neural and Symbolic ...

‪Gustav Šír‬ - ‪Google Scholar‬

Lifted relational neural networks: Efficient learning of latent relational structures. G Sourek, V Aschenbrenner, F Zelezny, S Schockaert, O Kuzelka. Journal of ...

Beyond Graph Neural Networks with PyNeuraLogic | by Gustav Šír

“Stacked structure learning for lifted relational neural networks.” International conference on inductive logic programming. Springer, Cham, ...

GustikS/GNNwLRNNs: Beyond Graph Neural Networks with Lifted ...

Beyond GNNs with LRNNs. This repository contains materials to reproduce the results from Beyond Graph Neural Networks with Lifted Relational Neural Networks.

Neural Networks for Relational Data

Our work is closest to Lifted Relational. Neural Networks (LRNN) [42] due to Šourek et al., in terms of the architecture. LRNN uses expert hand-crafted ...

Deep Learning with Relational Logic Representations - IJCAI

We have instantiated these principles in our framework of Lifted Relational Neural Net- ... Stacked structure learning for lifted relational neural networks. In.

Relational Neural Machines - Ecai 2020

aert, and Ondrej Kuzelka, 'Lifted relational neural networks: Efficient learning of latent relational structures', Journal of Artificial Intelligence.

Learning Lifted Operator Models with Logical Neural Networks

Abstract. We tackle the problem of relational model based reinforcement learning. Specifically, we are trying to learn lifted logical ...

Neural Networks for Relational Data - OUCI

Neural Networks for Relational Data. https://doi.org/10.1007/978-3-030-49210-6_6 ·. Journal: Inductive Logic Programming Lecture Notes in Computer Science, ...