881 citations · 968 across the 3 of their papers we have counts for
3 papers
cs.AI2011★ 21 cited
Towards Completely Lifted Search-based Probabilistic Inference
David Poole, Fahiem Bacchus, Jacek Kisynski
The promise of lifted probabilistic inference is to carry out probabilistic inference in a relational probabilistic model without needing to reason about each individual separately…
cs.AI2011★ 881 cited
CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements
C. Boutilier, R. I. Brafman, C. Domshlak +2
Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitati…
cs.AI2011★ 66 cited
Exploiting Contextual Independence In Probabilistic Inference
D. Poole, N. L. Zhang
Bayesian belief networks have grown to prominence because they provide compact representations for many problems for which probabilistic inference is appropriate, and there are alg…