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4Sequential updating of conditional probabilities on directed graphical structures
D. Spiegelhalter, and S. Lauritzen. Networks, 20 (5): 579--605 (1990)
13 years ago by @djain
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8The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks
G. Cooper. Artificial Intelligence, 42 (2-3): 393-405 (1990)
13 years ago by @djain
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2Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior
P. Hoyer, A. Hyvärinen, and A. Arinen. Advances in Neural Information Processing Systems, 15, (2002)
13 years ago by @djain
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cognition
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12Probabilistic Graphical Models - Principles and Techniques.
D. Koller, and N. Friedman. MIT Press, (2009)
13 years ago by @djain
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2Simulation Approaches to General Probabilistic Inference on Belief Networks.
R. Shachter, and M. Peot. UAI, page 221-234. North-Holland, (1989)
13 years ago by @djain
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3Learning First-Order Probabilistic Models with Combining Rules
S. Natarajan, P. Tadepalli, T. Dietterich, and A. Fern. Ann. Math. Artif. Intell., 54 (1-3): 223-256 (2008)
14 years ago by @djain
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4Relational Bayesian Networks
M. Jaeger. Proceedings of the 13th Annual Conference on Uncertainty in AI (UAI), page 266--273. Morgan Kaufmann, (1997)
14 years ago by @djain
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1Complex Probabilistic Modeling with Recursive Relational Bayesian Networks
M. Jaeger. Annals of Mathematics and Artificial Intelligence, 32 (1-4): 179--220 (2001)
14 years ago by @djain
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6MEBN: A Language for First-Order Bayesian Knowledge Bases
K. Laskey. Artif. Intell., 172 (2-3): 140--178 (2008)
14 years ago by @djain
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1Bayesian Logic Programming: Theory and Tool
K. Kersting, and L. Raedt. chapter 10, MIT Press, (2007)
14 years ago by @djain
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3SPOOK: A system for probabilistic object-oriented knowledge representation.
A. Pfeffer, D. Koller, B. Milch, and K. Takusagawa. UAI, page 541-550. Morgan Kaufmann, (1999)
14 years ago by @djain
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4Nonparametric Bayesian Logic.
P. Carbonetto, J. Kisynski, N. de Freitas, and D. Poole. UAI, page 85-93. AUAI Press, (2005)
14 years ago by @djain
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5BLOG: Probabilistic Models with Unknown Objects.
B. Milch, B. Marthi, S. Russell, D. Sontag, D. Ong, and A. Kolobov. Probabilistic, Logical and Relational Learning, volume 05051 of Dagstuhl Seminar Proceedings, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, (2005)
14 years ago by @djain
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BibSonomy

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publications (hide)13
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4Sequential updating of conditional probabilities on directed graphical structures

8The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks

2Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior

12Probabilistic Graphical Models - Principles and Techniques.

2Simulation Approaches to General Probabilistic Inference on Belief Networks.

3Learning First-Order Probabilistic Models with Combining Rules

4Relational Bayesian Networks

1Complex Probabilistic Modeling with Recursive Relational Bayesian Networks

6MEBN: A Language for First-Order Bayesian Knowledge Bases

1Bayesian Logic Programming: Theory and Tool

3SPOOK: A system for probabilistic object-oriented knowledge representation.

4Nonparametric Bayesian Logic.

5BLOG: Probabilistic Models with Unknown Objects.

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