83 citations · 616 across the 106 of their papers we have counts for
6 papers · 1 filter
Symmetric Weighted First-Order Model Counting
Paul Beame, Guy Van den Broeck, Eric Gribkoff +1
The FO Model Counting problem (FOMC) is the following: given a sentence in FO and a number , compute the number of models of over a domain of size ; the Weighted vari…
Lifted Probabilistic Inference for Asymmetric Graphical Models
Guy Van den Broeck, Mathias Niepert
Lifted probabilistic inference algorithms have been successfully applied to a large number of symmetric graphical models. Unfortunately, the majority of real-world graphical models…
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
Guy Van den Broeck, Karthika Mohan, Arthur Choi +1
We propose an efficient family of algorithms to learn the parameters of a Bayesian network from incomplete data. In contrast to textbook approaches such as EM and the gradient meth…
Understanding the Complexity of Lifted Inference and Asymmetric Weighted Model Counting
Eric Gribkoff, Guy Van den Broeck, Dan Suciu
In this paper we study lifted inference for the Weighted First-Order Model Counting problem (WFOMC), which counts the assignments that satisfy a given sentence in first-order logic…
On the Role of Canonicity in Bottom-up Knowledge Compilation
Guy Van den Broeck, Adnan Darwiche
We consider the problem of bottom-up compilation of knowledge bases, which is usually predicated on the existence of a polytime function for combining compilations using Boolean op…
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference
Mathias Niepert, Guy Van den Broeck
Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statist…