4 papers
Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Data
Arie Soeteman, Balder ten Cate, Maurice Funk +3
The conventional approach to deep learning over relational databases applies neural models, such as Graph Neural Networks (GNNs), to a graph representation of the database. Recent…
Expressive Power of Deep Homomorphism Networks over Relational Databases
Moritz Schönherr, Balder ten Cate, Maurice Funk +3
The expressive limitations of message-passing Graph Neural Networks (GNNs) have motivated a wide range of more powerful graph learning architectures. We advocate Deep Homomorphism…
Database Views as Explanations for Relational Deep Learning
Agapi Rissaki, Ilias Fountalis, Wolfgang Gatterbauer +1
In recent years, there has been significant progress in the development of deep learning models over relational databases, including architectures based on heterogeneous graph neur…
Using Database Dependencies to Constrain Approval-Based Committee Voting in the Presence of Context
Roi Yona, Benny Kimelfeld
In Approval-Based Committee (ABC) voting, each voter lists the candidates they approve and then a voting rule aggregates the individual approvals into a committee that represents t…