4 papers · 1 filter
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…
Extremal Fitting Problems for Conjunctive Queries
Balder ten Cate, Victor Dalmau, Maurice Funk +1
The fitting problem for conjunctive queries (CQs) is the problem to construct a CQ that fits a given set of labeled data examples. When a fitting CQ exists, it is in general not un…
Query Repairs
Balder ten Cate, Phokion Kolaitis, Carsten Lutz
We formalize and study the problem of repairing database queries based on user feedback in the form of a collection of labeled examples. We propose a framework based on the notion…