3 papers
cs.AI2025
Approximate Lifted Model Construction
Malte Luttermann, Jan Speller, Marcel Gehrke +3
Probabilistic relational models such as parametric factor graphs enable efficient (lifted) inference by exploiting the indistinguishability of objects. In lifted inference, a repre…
cs.AI2024
Towards Privacy-Preserving Relational Data Synthesis via Probabilistic Relational Models
Malte Luttermann, Ralf Möller, Mattis Hartwig
Probabilistic relational models provide a well-established formalism to combine first-order logic and probabilistic models, thereby allowing to represent relationships between obje…
cs.AI2024
Lifted Causal Inference in Relational Domains
Malte Luttermann, Mattis Hartwig, Tanya Braun +2
Lifted inference exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, thereby speeding up query answering while maintainin…