8 papers · 1 filter
Lifting Factor Graphs with Some Unknown Factors for New Individuals
Malte Luttermann, Ralf Möller, Marcel Gehrke
Lifting exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, allowing to carry out query answering more efficiently while…
Lifted Model Construction without Normalisation: A Vectorised Approach to Exploit Symmetries in Factor Graphs
Malte Luttermann, Ralf Möller, Marcel Gehrke
Lifted probabilistic inference exploits symmetries in a probabilistic model to allow for tractable probabilistic inference with respect to domain sizes of logical variables. We fou…
Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs
Malte Luttermann, Tanya Braun, Ralf Möller +1
Lifting uses a representative of indistinguishable individuals to exploit symmetries in probabilistic relational models, denoted as parametric factor graphs, to speed up inference…
Efficient Detection of Commutative Factors in Factor Graphs
Malte Luttermann, Johann Machemer, Marcel Gehrke
Lifted probabilistic inference exploits symmetries in probabilistic graphical models to allow for tractable probabilistic inference with respect to domain sizes. To exploit symmetr…
Lifting Factor Graphs with Some Unknown Factors
Malte Luttermann, Ralf Möller, Marcel Gehrke
Lifting exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, allowing to carry out query answering more efficiently while…
Efficient Detection of Exchangeable Factors in Factor Graphs
Malte Luttermann, Johann Machemer, Marcel Gehrke
To allow for tractable probabilistic inference with respect to domain sizes, lifted probabilistic inference exploits symmetries in probabilistic graphical models. However, checking…