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	A tutorial on learning with bayesian networks [My Copy] (# 1995) by D. Heckerman posted to learning graphical_model bayesian by ingo on 2009-11-17 16:24:40 as along with 44 people and 8 groups Sergey_gerbek Gorzomagnificent pwz mhofree soidis m0ta korakot A_Olympia neilernst JoSeK jrw waffle168 davidbroadhurst biplabbose tsprau2 garyfeng aufrank grimm okarsligil rkdeexit bayesian mystiphiliac kresala stvijayanand lyongu eustatic tystl wnpx ddahlem pverstra proportional llamerada torch eman_fcis cerkut tvdbulck jaspervoskuilen ajylha eacebo helsley pprett dcastro tessaverhoef frohike Philosophy_of_Information Blog_and_Wiki_Research mgh-lcs ReadingLab ur-cls Bioinformatics macc contact-id
	A joint model of regulatory and metabolic networks [My Copy] BMC Bioinformatics, Vol. 7, No. 1. (04 July 2006), 332. by Chen H. Yeang, Martin Vingron posted to perturbation network_refinement graphical_model by chasmand on 2009-11-11 18:50:11 as along with 6 people ptrobajo cgaugain schwartzjmc alexg cgaray roys
	Which graphical models are difficult to learn? [My Copy] (30 Oct 2009) by Jose Bento, Andrea Montanari posted to phase_transition learning ising graphical_model by marinari on 2009-11-10 09:10:40 as
	Understanding belief propagation and its generalizations [My Copy] (2003), pp. 239-269. by Jonathan S. Yedidia, William T. Freeman, Yair Weiss posted to graphical_model inference by wasteland93 on 2009-10-16 07:48:46 as along with 12 people FMZ Quixote robotact markusd bhaddow dowlingj rsantana ElQuijote42 zeppe lcigler mmcgloho matjes
	High-dimensional graphical model selection using ℓ1-regularized logistic regression [My Copy] In Advances in Neural Information Processing Systems 19 (2007), pp. 1465-1472. by Pradeep Ravikumar, John D. Lafferty posted to gm graphical_model model_selection by Vezhnick on 2009-07-16 10:23:51 as
	The Factored Frontier Algorithm for Approximate Inference in DBNs [My Copy] In Proceedings of the 17th Conference on Uncertainty in Artificial Intelligence (2001), pp. 378-385. by K. P. Murphy, Y. Weiss posted to graphical_model inference by wasteland93 on 2009-04-08 13:12:05 as along with 1 person espriggs
	Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets [My Copy] Journal of Artificial Intelligence Research, Vol. 8 (1998), pp. 67-91. by Andrew Moore, Mary S. Lee posted to graphical_model data learning by wasteland93 on 2009-04-03 17:29:11 as
	Exploiting causal independence in bayesian network inference [My Copy] Journal of Artificial Intelligence Research, Vol. 5 (1996), pp. 301-328. by Nevin L. Zhang, David Poole posted to graphical_model inference by wasteland93 on 2008-10-07 10:57:31 as
	Bayesian Graphical Models for Discrete Data [My Copy] International Statistical Review / Revue Internationale de Statistique, Vol. 63, No. 2. (1995), pp. 215-232. by David Madigan, Jeremy York, Denis Allard posted to bayesian graphical_model mcmc by naegele on 2008-08-13 14:22:45 as along with 2 people fordela slygent
	Bayes net graphs to understand co-authorship networks? [My Copy] In LinkKDD '05: Proceedings of the 3rd international workshop on Link discovery (2005), pp. 1-8. by Anna Goldenberg, Andrew W. Moore posted to bayesian_network coauthorship graphical_model structure_learning by naegele on 2008-07-30 10:20:22 as along with 1 person Repton
	Expert Systems and Probabilistic Network Models [My Copy] (13 December 1996) by Enrique Castillo, José M. Gutiérrez, Ali S. Hadi posted to graphical_model by naegele on 2008-07-07 14:02:35 as along with 2 people elsantosneto wasteland93
	Clustering Without (Thinking About) Triangulation [My Copy] (1995) by D. Denise posted to graphical_model inference by wasteland93 on 2008-05-22 12:04:15 as
	Operations for inference in continuous Bayesian networks with linear deterministic variables [My Copy] International Journal of Approximate Reasoning In PGM'04, Vol. 42, No. 1-2. (May 2006), pp. 21-36. by Barry R. Cobb, Prakash P. Shenoy posted to graphical_model inference by wasteland93 on 2008-04-30 09:15:02 as
	Operating with potentials of discrete variables [My Copy] International Journal of Approximate Reasoning In Special Section: Random Sets and Imprecise Probabilities (Issues in Imprecise Probability), Vol. 46, No. 1. (September 2007), pp. 166-187. by M. Arias, F. J. Díez posted to graphical_model inference by wasteland93 on 2008-04-30 09:10:25 as
	Bayesian networks in reliability [My Copy] Reliability Engineering & System Safety, Vol. 92, No. 1. (January 2007), pp. 92-108. by Helge Langseth, Luigi Portinale posted to graphical_model reliability by wasteland93 on 2007-10-10 09:27:32 as
	Inferring cellular networks - a review [My Copy] BMC Bioinformatics, Vol. 8, No. Suppl 6. (2007), S5. by Florian Markowetz, Rainer Spang posted to graphical_model network by dejori on 2007-10-01 13:13:16 as along with 15 people jaspervoskuilen antonkratz daforerog chica ocs roys cswinburne ndiaz edwardmorrissey guhjy tmmurali shigepong heliopais bertelsen czeller
	Loopy Belief Propagation for Approximate Inference: An Empirical Study [My Copy] In Proceedings of the 15th on Uncertainty in Artificial Intelligence (1999), pp. 467-475. by K. P. Murphy, Y. Weiss, M. I. Jordan posted to graphical_model inference by wasteland93 on 2007-09-24 16:28:09 as along with 5 people markusd zeppe bhaddow rsantana dlmace
	Tractable Inference for Complex Stochastic Processes [My Copy] In Uncertainty in artificial Intelligence (July 1998), pp. 32-42. by X. Boyen, D. Koller posted to graphical_model inference by wasteland93 on 2007-09-24 13:24:21 as
	The computational complexity of probabilistic inference using bayesian belief networks [My Copy] Artificial Intelligence, Vol. 42, No. 2-3. (March 1990), pp. 393-405. by G. F. Cooper posted to graphical_model inference by wasteland93 on 2007-09-24 12:08:54 as along with 2 people and 1 group mhay lcigler kdl
	Fusion, propagation, and structuring in belief networks [My Copy] Artificial Intelligence, Vol. 29, No. 3. (September 1986), pp. 241-288. by J. Pearl posted to graphical_model inference by wasteland93 on 2007-09-24 12:04:06 as along with 4 people Maderlock thienanh lcigler dcoates
	A DBN inference algorithm using junction tree [My Copy] Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on In Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on, Vol. 5 (2004), pp. 4236-4240 Vol.5. by Fengzhan Tian, Yuchang Lu posted to graphical_model dynamic inference by wasteland93 on 2007-09-21 16:33:36 as along with 1 person Maderlock
	Identifying interventional and pathogenic mechanisms by generative inverse modeling of gene expression profiles. [My Copy] J Comput Biol, Vol. 11, No. 6. (2004), pp. 1135-1148. by M. Dejori, M. Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group generif_paper on 2007-09-05 12:23:19 as
	Hunting drug targets by systems-level modeling of gene expression profiles. [My Copy] IEEE Trans Nanobioscience, Vol. 3, No. 3. (September 2004), pp. 180-191. by M. Dejori, B. Schuermann, M. Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group generif_paper on 2007-09-05 12:22:39 as along with 1 person and 1 group frohike ic4
	Mining Functional Modules in Genetic Networks with Decomposable Graphical Models [My Copy] OMICS: A Journal of Integrative Biology, Vol. 8, No. 2. (July 2004), pp. 176-188. by Mathaus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group generif_paper on 2007-09-05 12:21:55 as along with 3 people and 1 group tjtaylor rsantana DavidEdwards ic4
	Automatically translating dynamic fault trees into dynamic Bayesian networks by means of a software tool [My Copy] Availability, Reliability and Security, 2006. ARES 2006. The First International Conference on In Proceedings of the First International Conference on Availability, Reliability and Security (April 2006), pp. 804-809. by S. Montani, L. Portinale, A. Bobbio, D. Codetta-Raiteri posted to graphical_model dynamic fault_trees by wasteland93 on 2007-08-28 14:33:58 as
	An Introduction to Variational Methods for Graphical Models [My Copy] Machine Learning, Vol. 37, No. 2. (1 November 1999), pp. 183-233. by M. Jordan, Z. Ghahramani, T. S. Jaakkola, L. K. Saul posted to graphical_model inference by wasteland93 on 2007-07-30 15:46:01 as along with 9 people zhengyun bertelsen ktsianos ppeeling arthur ldietz Ayest wnpx asterix77
	Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems [My Copy] Journal of the Royal Statistical Society, Vol. 50, No. 2. (1988), pp. 157-224. by S. L. Lauritzen, D. J. Spiegelhalter posted to graphical_model inference by wasteland93 on 2007-07-30 12:39:52 as along with 7 people Viperus zeppe frohike tmmurali sutovsky lcigler roys
	Bucket Elimination: A Unifying Framework for Reasoning [My Copy] Artificial Intelligence, Vol. 113, No. 1-2. (1999), pp. 41-85. by R. Dechter posted to graphical_model inference by wasteland93 on 2007-07-27 10:09:03 as along with 1 person lcigler
	Bayesian networks for multilevel system reliability [My Copy] Reliability Engineering & System Safety, Vol. 92, No. 10. (October 2007), pp. 1413-1420. by Alyson G. Wilson, Aparna V. Huzurbazar posted to graphical_model inference reliability by wasteland93 on 2007-07-23 14:01:43 as
	Learning Bayesian Networks from Incomplete Databases [My Copy] (1997), pp. 401-408. by Marco Ramoni, Paola Sebastiani posted to graphical_model learning by wasteland93 on 2007-05-28 15:20:45 as
	Learning Gaussian Networks [My Copy] No. MSR-TR-94-10. (1994) by Dan Geiger, David Heckerman posted to bayes graphical_model by dimatura on 2007-05-22 11:30:50 as along with 2 people and 1 group bpacker pliz vision-ng
	A tutorial on learning with bayesian networks [My Copy] (1995) by D. Heckerman posted to bayes graphical_model by dimatura on 2007-05-22 11:30:10 as along with 9 people tvdbulck ldfu wnpx macle sugarexpletive mistersheik markusd pgan delip
	Feature Subset Selection by Bayesian network-based optimization [My Copy] Artificial Intelligence, Vol. 123, No. 1-2. (2000), pp. 157-184. by Inaki Inza, Pedro Larranaga, R. Etxeberria, Basilio Sierra posted to bayes feature_selection graphical_model by dimatura on 2007-05-22 11:29:32 as along with 2 people wnpx eacosta
	HMMs and coupled HMMs for multi-channel EEG classification [My Copy] (2002) by S. Zhong, J. Ghosh posted to bci graphical_model by dimatura on 2007-05-22 10:04:22 as
	Modelling gene expression data using dynamic Bayesian networks [My Copy] (1999) by K. Murphy, S. Mian posted to bayes graphical_model microarray time_series by dimatura on 2007-05-22 09:26:09 as along with 3 people frohike arider1 wnpx
	Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. [My Copy] Nature genetics, Vol. 34, No. 2. (11 June 2003), pp. 166-176. by Eran Segal, Michael Shapira, Aviv Regev, et al.Dana Pe'er, David Botstein, Daphne Koller, Nir Friedman posted to bayes graphical_model microarray by dimatura on 2007-05-22 08:51:04 as along with 27 people and 1 group meanerelk chasmand stharward bertelsen ipark-kaist VGreiff benjaminsb wangbo ajbattle cswinburne ggallone ealloza orzenil tuck bayesian wnpx tabu koller olympos fishtank karfunkel roys pkm dragonrez tvdbulck chrisamiller aviad_work Jarman Lab
	Graphical Models [My Copy] (2003) by M. Jordan posted to graphical_model by dimatura on 2007-05-18 18:16:15 as along with 2 people markusd naegele
	Bayesian Graphical Models for Adaptive Filtering [My Copy] by Yi Zhang posted to bayes feature_selection graphical_model by dimatura on 2007-05-18 13:04:31 as along with 1 person sugarexpletive
	Bayesian network learning with parameter constraints [My Copy] (2006) by R. Niculescu, T. Mitchell posted to graphical_model by dimatura on 2007-05-18 09:02:16 as
	Learning module networks [My Copy] (2003) by E. Segal, D. Pe'er, A. Regev, D. Koller, N. Friedman posted to graphical_model by dimatura on 2007-05-18 08:59:01 as along with 2 people tvdbulck roys
	Learning Bayesian Network Structure from Massive Datasets: The ”Sparse Candidate” Algorithm [My Copy] pp. 206-215. by Nir Friedman, Iftach Nachman, Dana Peér posted to graphical_model by dimatura on 2007-05-18 08:58:30 as
	Using Bayesian networks to analyze expression data [My Copy] In RECOMB (2000), pp. 127-135. by Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er posted to graphical_model microarray by dimatura on 2007-05-18 08:55:42 as
	Learning Bayesian Network Structure from Massive Datasets: The ”Sparse Candidate” Algorithm [My Copy] pp. 206-215. by Nir Friedman, Iftach Nachman, Dana Peér posted to bayes graphical_model by dimatura on 2007-05-17 20:26:32 as along with 4 people ldfu wnpx famoreira roys
	Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks [My Copy] (January 2003) by N. Friedman, D. Koller posted to bayes clustering graphical_model by dimatura on 2007-05-17 20:25:55 as along with 7 people oyen markusd zeppe abhik eustatic wnpx yoh
	Multivariate information bottleneck [My Copy] Neural Comput., Vol. 18, No. 8. (August 2006), pp. 1739-1789. by Noam Slonim, Nir Friedman, Naftali Tishby posted to clustering graphical_model microarray by dimatura on 2007-05-17 20:25:32 as along with 1 person zhengyun
	Inferring Cellular Networks Using Probabilistic Graphical Models [My Copy] Science, Vol. 303, No. 5659. (6 February 2004), pp. 799-805. by Nir Friedman posted to bayes clustering graphical_model microarray by dimatura on 2007-05-17 19:54:27 as along with 24 people and 2 groups antonkratz jxl phoenixzxl abhishek_tiwari richardbickerton ruichu ggallone bertelsen ldfu ujh lfriedl opheliav ryang wnpx nirfriedman neveaire koller helsley edwardmorrissey vietanh0 Yumyai srp33 saman_vp jo_davies Jarman Lab kdl
	Probabilistic reasoning in intelligent systems : networks of plausible inference [My Copy] (15 September 1988) by J. Pearl posted to graphical_model inference by wasteland93 on 2007-04-10 08:49:08 as along with 18 people dglane001 alexander_bauer psychorav rockelegancy mthomure pprett tvdbulck tdlt leidner pcarbo fheintz wnpx fsteeg lcigler 1like naegele quianominorleo robotact
	The Bayes Net Toolbox for MATLAB [My Copy] (2001) by Murphy P. Kevin posted to graphical_model software by wasteland93 on 2007-03-08 12:41:03 as along with 3 people and 1 group hawkes A_Olympia wnpx logics of knowledge
	Learning Bayesian Networks [My Copy] (01 April 2003) by Richard E. Neapolitan posted to graphical_model learning by wasteland93 on 2007-02-20 15:51:33 as along with 10 people and 1 group tvdbulck ldfu garyfeng balicea wnpx harriscd naegele quianominorleo czeller abellogin ReadingLab
	Improving the analysis of dependable systems by mapping fault trees into Bayesian networks [My Copy] Reliability Engineering & System Safety, Vol. 71, No. 3. (March 2001), pp. 249-260. by A. Bobbio, L. Portinale, M. Minichino, E. Ciancamerla posted to modelling graphical_model fault_trees by wasteland93 on 2007-01-23 12:49:36 as

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