collaborators

7 papers

cs.LG2026

The Boolean Power of ReLU

Pablo Barceló, Floris Geerts, Matthias Lanzinger +2

We prove that, on finite simple undirected graphs equipped with a single Boolean node feature, the Boolean queries expressible in -MPLang, for any collection of eventually c…

cs.DB2026

The KG-ER Conceptual Schema Language

Enrico Franconi, Benoît Groz, Jan Hidders +4

We propose KG-ER, a conceptual schema language for knowledge graphs that describes the structure of knowledge graphs independently of their representation (relational databases, pr…

cs.DB2026

MLSkip: Data Skipping for ML Filters via Lightweight Metadata

Mihail Stoian, Mark Gerarts, Pascal Ginter +3

Database vendors recently released AI functions that can be used in filter predicates. As such functions often rely on costly, black-box ML models, they unveil new data management…

cs.LG2026

A Logical View of GNN-Style Computation and the Role of Activation Functions

Pablo Barceló, Floris Geerts, Matthias Lanzinger +2

We study the numerical and Boolean expressiveness of MPLang, a declarative language that captures the computation of graph neural networks (GNNs) through linear message passing and…

cs.DB2026

On the generic information capacity of relational schemas with a single binary relation

Benoît Groz, Jan Hidders, Nina Pardal +2

We consider database schemas consisting of a single binary relation, with key constraints and inclusion dependencies. Over this space of 20 schemas, we completely characterize when…

cs.LO2026

Recursive querying of neural networks via weighted structures

Martin Grohe, Christoph Standke, Juno Steegmans +1

Expressive querying of machine learning models - viewed as a form of intentional data - enables their verification and interpretation using declarative languages, thereby making le…