| Probabilistic conditional independence structures M Studeny Springer Science & Business Media, 2006 | 364 | 2006 |
| The multiinformation function as a tool for measuring stochastic dependence M Studený, J Vejnarová Learning in graphical models, 261-297, 1998 | 235 | 1998 |
| Conditional independence relations have no finite complete characterization M Studený Information Theory, Statistical Decision Functions and Random Processes …, 1992 | 206 | 1992 |
| Multiinformation and the problem of characterization of conditional independence relations M SruoBNÝ | 116 | 1989 |
| On chain graph models for description of conditional independence structures M Studeny, RR Bouckaert Annals of Statistics, 1434-1495, 1998 | 109 | 1998 |
| Conditional independences among four random variables I F Matúš, M Studený Combinatorics, Probability and Computing 4 (3), 269-278, 1995 | 107 | 1995 |
| Formal properties of conditional independence in different calculi of AI M Studený Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European …, 1993 | 89 | 1993 |
| A recovery algorithm for chain graphs M Studený International Journal of Approximate Reasoning 17 (2-3), 265-293, 1997 | 69 | 1997 |
| Semigraphoids and structures of probabilistic conditional independence M Studený Annals of Mathematics and Artificial Intelligence 21, 71-98, 1997 | 52 | 1997 |
| Characteristic imsets for learning Bayesian network structure R Hemmecke, S Lindner, M Studený International Journal of Approximate Reasoning 53 (9), 1336-1349, 2012 | 51 | 2012 |
| Bayesian networks from the point of view of chain graphs M Studeny arXiv preprint arXiv:1301.7414, 2013 | 50 | 2013 |
| A graphical characterization of the largest chain graphs M Volf, M Studený International Journal of Approximate Reasoning 20 (3), 209-236, 1999 | 45 | 1999 |
| A geometric view on learning Bayesian network structures M Studený, J Vomlel, R Hemmecke International Journal of Approximate Reasoning 51 (5), 573-586, 2010 | 40 | 2010 |
| Polyhedral aspects of score equivalence in Bayesian network structure learning J Cussens, D Haws, M Studený Mathematical Programming 164, 285-324, 2017 | 39 | 2017 |
| Chain graphs: semantics and expressiveness RR Bouckaert, M Studený Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European …, 1995 | 36 | 1995 |
| 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 | 34 | 1997 |
| Attempts at axiomatic description of conditional independence M Studený Kybernetika 25 (7), 72-79, 1989 | 33 | 1989 |
| Complexity of structural models M Studeny Prague stochastics' 98 (23-28 August 1998), 1998 | 32 | 1998 |
| 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 | 31 | 2010 |
| Extreme supermodular set functions over five variables M Studený, RR Bouckaert, T Kocka Institute of Information Theory and Automation, 2000 | 29 | 2000 |
Remco BouckaertVerified email at cs.auckland.ac.nz
