Graphical Models

symmetries. Measures of volume, compactness, or convexity. Morphological operations (offsetting, rounding, tightening)

[1]  T. Nakashizuka,et al.  Mortality due to Japanese oak wilt disease and surrounding forest compositions , 2015, Data in brief.

[2]  Hilbert J. Kappen,et al.  General Lower Bounds based on Computer Generated Higher Order Expansions , 2012, UAI.

[3]  Seth Sullivant,et al.  Identifying Causal Effects with Computer Algebra , 2010, UAI.

[4]  Seth Sullivant,et al.  Lectures on Algebraic Statistics , 2008 .

[5]  Michael I. Jordan,et al.  Graphical Models, Exponential Families, and Variational Inference , 2008, Found. Trends Mach. Learn..

[6]  S. Sullivant,et al.  Trek separation for Gaussian graphical models , 2008, 0812.1938.

[7]  Grégoire Lecerf,et al.  Lifting and recombination techniques for absolute factorization , 2007, J. Complex..

[8]  Seth Sullivant,et al.  Algebraic geometry of Gaussian Bayesian networks , 2007, Adv. Appl. Math..

[9]  D. Geiger,et al.  On the toric algebra of graphical models , 2006, math/0608054.

[10]  Christian Schlegel,et al.  Low-Density Parity-Check Codes , 2004 .

[11]  D. M. Titterington,et al.  Bayesian Methods for Neural Networks and Related Models , 2004 .

[12]  Martin J. Wainwright,et al.  Semidefinite Relaxations for Approximate Inference on Graphs with Cycles , 2003, NIPS.

[13]  T. Speed,et al.  Biological Sequence Analysis , 1998 .

[14]  B. Sturmfels,et al.  Algebraic geometry of Bayesian networks , 2003, J. Symb. Comput..

[15]  Tim Hesterberg,et al.  Monte Carlo Strategies in Scientific Computing , 2002, Technometrics.

[16]  Jeff A. Bilmes,et al.  Graphical models and automatic speech recognition , 2002 .

[17]  P. Green,et al.  Mixture models in measurement error problems, with reference to epidemiological studies , 2002 .

[18]  Sekhar Tatikonda,et al.  Loopy Belief Propogation and Gibbs Measures , 2002, UAI.

[19]  Jonathan P. Bollback,et al.  Empirical and hierarchical Bayesian estimation of ancestral states. , 2001, Systematic biology.

[20]  Rüdiger L. Urbanke,et al.  Design of capacity-approaching irregular low-density parity-check codes , 2001, IEEE Trans. Inf. Theory.

[21]  B. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[22]  Kevin P. Murphy,et al.  Linear-time inference in Hierarchical HMMs , 2001, NIPS.

[23]  Hoon Kim,et al.  Monte Carlo Statistical Methods , 2000, Technometrics.

[24]  Alun Thomas,et al.  Multilocus linkage analysis by blocked Gibbs sampling , 2000, Stat. Comput..

[25]  T. Richardson,et al.  Design of provably good low-density parity check codes , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[26]  Hagai Attias,et al.  A Variational Bayesian Framework for Graphical Models , 1999 .

[27]  Michael I. Jordan,et al.  Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones , 1999, Machine Learning.

[28]  David J. Spiegelhalter,et al.  Probabilistic Networks and Expert Systems , 1999, Information Science and Statistics.

[29]  Michael I. Jordan,et al.  An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.

[30]  Dana Ron,et al.  The power of amnesia: Learning probabilistic automata with variable memory length , 1996, Machine Learning.

[31]  Michael I. Jordan,et al.  Reinforcement Learning by Probability Matching , 1995, NIPS 1995.

[32]  Uffe Kjærulff,et al.  Blocking Gibbs sampling in very large probabilistic expert systems , 1995, Int. J. Hum. Comput. Stud..

[33]  Walter R. Gilks,et al.  A Language and Program for Complex Bayesian Modelling , 1994 .

[34]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[35]  Prakash P. Shenoy,et al.  Axioms for probability and belief-function proagation , 1990, UAI.

[36]  Derek G. Corneil,et al.  Complexity of finding embeddings in a k -tree , 1987 .

[37]  E. Lander,et al.  Construction of multilocus genetic linkage maps in humans. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[38]  R. Elston,et al.  A general model for the genetic analysis of pedigree data. , 1971, Human heredity.

[39]  Jessika Weiss,et al.  Graphical Models In Applied Multivariate Statistics , 2016 .

[40]  Wray L. Buntine,et al.  Graphical Models , 2010, Encyclopedia of Machine Learning and Data Mining.

[41]  Sunita Sarawagi.  Learning with Graphical Models , 2008 .

[42]  J. Felsenstein.  Evolutionary trees from DNA sequences: A maximum likelihood approach , 2005, Journal of Molecular Evolution.

[43]  Michael I. Jordan,et al.  Hierarchical Bayesian Models for Applications in Information Retrieval , 2003 .

[44]  Stuart J. Russell,et al.  Dynamic bayesian networks: representation, inference and learning , 2002 .

[45]  X. Jin.  Factor graphs and the Sum-Product Algorithm , 2002 .

[46]  Tom Minka,et al.  A family of algorithms for approximate Bayesian inference , 2001 .

[47]  W. Freeman,et al.  Generalized Belief Propagation , 2000, NIPS.

[48]  Robert J. McEliece,et al.  The generalized distributive law , 2000, IEEE Trans. Inf. Theory.

[49]  Zoubin Ghahramani,et al.  Propagation Algorithms for Variational Bayesian Learning , 2000, NIPS.

[50]  Michael I. Jordan,et al.  Boltzmann Chains and Hidden Markov Models , 1994, NIPS.