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Milan Studeny
Milan Studeny
Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic
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Probabilistic conditional independence structures
M Studeny
Springer Science & Business Media, 2006
3632006
The multiinformation function as a tool for measuring stochastic dependence
M Studený, J Vejnarová
Learning in graphical models, 261-297, 1998
2351998
Conditional independence relations have no finite complete characterization
M Studený
Information Theory, Statistical Decision Functions and Random Processes …, 1992
2051992
Multiinformation and the problem of characterization of conditional independence relations
M SruoBNÝ
1161989
On chain graph models for description of conditional independence structures
M Studeny, RR Bouckaert
Annals of Statistics, 1434-1495, 1998
1091998
Conditional independences among four random variables I
F Matúš, M Studený
Combinatorics, Probability and Computing 4 (3), 269-278, 1995
1071995
Formal properties of conditional independence in different calculi of AI
M Studený
Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European …, 1993
891993
A recovery algorithm for chain graphs
M Studený
International Journal of Approximate Reasoning 17 (2-3), 265-293, 1997
691997
Characteristic imsets for learning Bayesian network structure
R Hemmecke, S Lindner, M Studený
International Journal of Approximate Reasoning 53 (9), 1336-1349, 2012
512012
Semigraphoids and structures of probabilistic conditional independence
M Studený
Annals of Mathematics and Artificial Intelligence 21, 71-98, 1997
511997
Bayesian networks from the point of view of chain graphs
M Studeny
arXiv preprint arXiv:1301.7414, 2013
502013
A graphical characterization of the largest chain graphs
M Volf, M Studený
International Journal of Approximate Reasoning 20 (3), 209-236, 1999
451999
A geometric view on learning Bayesian network structures
M Studený, J Vomlel, R Hemmecke
International Journal of Approximate Reasoning 51 (5), 573-586, 2010
402010
Polyhedral aspects of score equivalence in Bayesian network structure learning
J Cussens, D Haws, M Studený
Mathematical Programming 164, 285-324, 2017
392017
Chain graphs: semantics and expressiveness
RR Bouckaert, M Studený
Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European …, 1995
361995
Information theoretical approach to constitution and reduction of medical data
J Zvárová, M Studený
International Journal of Medical Informatics 45 (1-2), 65-74, 1997
341997
Attempts at axiomatic description of conditional independence
M Studený
Kybernetika 25 (7), 72-79, 1989
331989
Complexity of structural models
M Studeny
Prague stochastics' 98 (23-28 August 1998), 1998
321998
Characteristic imset: a simple algebraic representative of a Bayesian network structure
M Studený, R Hemmecke, S Lindner
Proceedings of the 5th European workshop on probabilistic graphical models …, 2010
312010
Extreme supermodular set functions over five variables
M Studený, RR Bouckaert, T Kocka
Institute of Information Theory and Automation, 2000
292000
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