10 citations · 12 across the 9 of their papers we have counts for
5 papers · 1 filter
Understanding Domain-Size Generalization in Markov Logic Networks
Florian Chen, Felix Weitkämper, Sagar Malhotra
We study the generalization behavior of Markov Logic Networks (MLNs) across relational structures of different sizes. Multiple works have noticed that MLNs learned on a given domai…
Lifted Inference beyond First-Order Logic
Sagar Malhotra, Davide Bizzaro, Luciano Serafini
Weighted First Order Model Counting (WFOMC) is fundamental to probabilistic inference in statistical relational learning models. As WFOMC is known to be intractable in general ($\#…
Weighted First Order Model Counting with Directed Acyclic Graph Axioms
Sagar Malhotra, Luciano Serafini
Statistical Relational Learning (SRL) integrates First-Order Logic (FOL) and probability theory for learning and inference over relational data. Probabilistic inference and learnin…
On Projectivity in Markov Logic Networks
Sagar Malhotra, Luciano Serafini
Markov Logic Networks (MLNs) define a probability distribution on relational structures over varying domain sizes. Many works have noticed that MLNs, like many other relational mod…
Weighted Model Counting in the two variable fragment with Cardinality Constraints: A Closed Form Formula
Sagar Malhotra, Luciano Serafini
Weighted First-Order Model Counting (WFOMC) computes the weighted sum of the models of a first-order theory on a given finite domain. WFOMC has emerged as a fundamental tool for pr…