| Bayesian network learning with cutting planes J Cussens Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence …, 2011 | 314 | 2011 |
| Parameter estimation in stochastic logic programs J Cussens Machine Learning 44, 245-271, 2001 | 188 | 2001 |
| Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007 | 178 | 2007 |
| Integer linear programming for the Bayesian network structure learning problem M Bartlett, J Cussens Artificial Intelligence 244, 258-271, 2017 | 177 | 2017 |
| CLP(BN): Constraint Logic Programming for Probabilistic Knowledge V Santos Costa, D Page, J Cussens Probabilistic inductive logic programming, 156-188, 2008 | 167* | 2008 |
| Advances in Bayesian network learning using integer programming M Bartlett, J Cussens arXiv preprint arXiv:1309.6825, 2013 | 141 | 2013 |
| CLP(BN): Constraint logic programming for probabilistic knowledge V Santos Costa, D Page, M Qazi, J Cussens Proceedings of the nineteenth conference on uncertainty in artificial …, 2002 | 138* | 2002 |
| Part-of-speech tagging using Progol J Cussens International conference on inductive logic programming, 93-108, 1997 | 108 | 1997 |
| Predicting persistent depressive symptoms in older adults: a machine learning approach to personalised mental healthcare CM Hatton, LW Paton, D McMillan, J Cussens, S Gilbody, PA Tiffin Journal of affective disorders 246, 857-860, 2019 | 96 | 2019 |
| Loglinear models for first-order probabilistic reasoning J Cussens Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence …, 1999 | 79* | 1999 |
| Bayes and pseudo-Bayes estimates of conditional probabilities and their reliability J Cussens European Conference on Machine Learning, 136-152, 1993 | 70 | 1993 |
| Stochastic logic programs: Sampling, inference and applications J Cussens arXiv preprint arXiv:1301.3846, 2013 | 69 | 2013 |
| Bayesian network structure learning with integer programming: Polytopes, facets and complexity J Cussens, M Järvisalo, JH Korhonen, M Bartlett Journal of Artificial Intelligence Research 58, 185-229, 2017 | 65 | 2017 |
| Bayesian network learning by compiling to weighted MAX-SAT J Cussens arXiv preprint arXiv:1206.3244, 2012 | 60 | 2012 |
| Maximum likelihood pedigree reconstruction using integer linear programming J Cussens, M Bartlett, EM Jones, NA Sheehan Genetic epidemiology 37 (1), 69-83, 2013 | 50 | 2013 |
| Bayesian learning of Bayesian networks with informative priors N Angelopoulos, J Cussens Annals of Mathematics and Artificial Intelligence 54, 53-98, 2008 | 44 | 2008 |
| Searching multiregression dynamic models of resting-state fMRI networks using integer programming L Costa, J Smith, T Nichols, J Cussens, EP Duff, TR Makin | 43 | 2015 |
| Polyhedral aspects of score equivalence in Bayesian network structure learning J Cussens, D Haws, M Studený Mathematical Programming 164, 285-324, 2017 | 41 | 2017 |
| Exact estimation of multiple directed acyclic graphs CJ Oates, JQ Smith, S Mukherjee, J Cussens Statistics and Computing 26, 797-811, 2016 | 39 | 2016 |
| Learning language in logic J Cussens, S Dzeroski Springer Science & Business Media, 2000 | 38 | 2000 |
Mark BartlettSchool of Computing, Robert Gordon UniversityVerified email at rgu.ac.uk
