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» Adaptive inference on general graphical models
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CORR
2006
Springer
104views Education» more  CORR 2006»
14 years 9 months ago
Loop corrections for approximate inference
We propose a method to improve approximate inference methods by correcting for the influence of loops in the graphical model. The method is a generalization and alternative implem...
Joris M. Mooij, Bert Kappen
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 2 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
RT
2001
Springer
15 years 1 months ago
Realistic Reflections and Refractions on Graphics Hardware with Hybrid Rendering and Layered Environment Maps
We introduce hybrid rendering, a scheme that dynamically ray traces the local geometry of reflective and refractive objects, but approximates more distant geometry by hardwaresupp...
Ziyad S. Hakura, John M. Snyder
ICIG
2009
IEEE
15 years 4 months ago
Discriminative Maximum Margin Image Object Categorization with Exact Inference
Categorizing multiple objects in images is essentially a structured prediction problem: the label of an object is in general dependent on the labels of other objects in the image....
Qinfeng Shi, Luping Zhou, Li Cheng, Dale Schuurman...
IJCAI
2003
14 years 10 months ago
First-order probabilistic inference
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
David Poole