393 citations · 634 across the 19 of their papers we have counts for
3 papers · 1 filter
New Liftable Classes for First-Order Probabilistic Inference
Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck +1
Statistical relational models provide compact encodings of probabilistic dependencies in relational domains, but result in highly intractable graphical models. The goal of lifted i…
A Learning Algorithm for Relational Logistic Regression: Preliminary Results
Bahare Fatemi, Seyed Mehran Kazemi, David Poole
Relational logistic regression (RLR) is a representation of conditional probability in terms of weighted formulae for modelling multi-relational data. In this paper, we develop a l…
Why is Compiling Lifted Inference into a Low-Level Language so Effective?
Seyed Mehran Kazemi, David Poole
First-order knowledge compilation techniques have proven efficient for lifted inference. They compile a relational probability model into a target circuit on which many inference q…