| Order of nonlinearity as a complexity measure for models generated by symbolic regression via pareto genetic programming EJ Vladislavleva, GF Smits, D Den Hertog IEEE Transactions on Evolutionary Computation 13 (2), 333-349, 2008 | 390 | 2008 |
| Predicting the energy output of wind farms based on weather data: Important variables and their correlation E Vladislavleva, T Friedrich, F Neumann, M Wagner Renewable energy 50, 236-243, 2013 | 103 | 2013 |
| Constructing a no-reference H. 264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression N Staelens, D Deschrijver, E Vladislavleva, B Vermeulen, T Dhaene, ... IEEE Transactions on Circuits and Systems for Video Technology 23 (8), 1322-1333, 2013 | 80 | 2013 |
| Variable selection in industrial datasets using pareto genetic programming G Smits, A Kordon, K Vladislavleva, E Jordaan, M Kotanchek Genetic Programming Theory and Practice III, 79-92, 2006 | 71 | 2006 |
| Model-based problem solving through symbolic regression via pareto genetic programming E Vladislavleva | 66 | 2008 |
| Trustable symbolic regression models: using ensembles, interval arithmetic and pareto fronts to develop robust and trust-aware models M Kotanchek, G Smits, E Vladislavleva Genetic programming theory and practice V, 201-220, 2008 | 62 | 2008 |
| Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression S Stijven, W Minnebo, K Vladislavleva Proceedings of the 13th annual conference companion on Genetic and …, 2011 | 51 | 2011 |
| Symbolic regression via genetic programming as a discovery engine: Insights on outliers and prototypes ME Kotanchek, EY Vladislavleva, GF Smits Genetic Programming Theory and Practice VII, 55-72, 2010 | 50 | 2010 |
| On the importance of data balancing for symbolic regression E Vladislavleva, G Smits, D Den Hertog IEEE Transactions on Evolutionary Computation 14 (2), 252-277, 2009 | 49 | 2009 |
| Pursuing the Pareto paradigm: tournaments, algorithm variations and ordinal optimization M Kotanchek, G Smits, E Vladislavleva Genetic Programming Theory and Practice IV, 167-185, 2007 | 49 | 2007 |
| Active Learning to Understand Infectious Disease Models and Improve Policy Making L Willem, S Stijven, E Vladislavleva, J Broeckhove, P Beutels, N Hens PLOS Computational Biology, 2014 | 41 | 2014 |
| Genetic programming theory and practice VIII R Riolo, T McConaghy, E Vladislavleva Springer Science & Business Media, 2010 | 38 | 2010 |
| Ordinal pareto genetic programming G Smits, E Vladislavleva 2006 IEEE International Conference on Evolutionary Computation, 3114-3120, 2006 | 29 | 2006 |
| Genetic programming theory and practice 2010: An introduction T McConaghy, E Vladislavleva, R Riolo Genetic Programming Theory and Practice VIII 8, 2010 | 19 | 2010 |
| Prime-time: Symbolic regression takes its place in the real world S Stijven, E Vladislavleva, A Kordon, L Willem, ME Kotanchek Genetic Programming Theory and Practice XIII, 241-260, 2016 | 18 | 2016 |
| Genetic Programming Theory and Practice IX JH Moore, R Riolo, E Vladislavleva Springer, 2011 | 17 | 2011 |
| Knowledge mining with genetic programming methods for variable selection in flavor design K Vladislavleva, K Veeramachaneni, M Burland, J Parcon, UM O'Reilly Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 17 | 2010 |
| Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization K Veeramachaneni, E Vladislavleva, UM O’Reilly Genetic Programming and Evolvable Machines 13, 103-133, 2012 | 16 | 2012 |
| Scalable symbolic regression by continuous evolution with very small populations GF Smits, E Vladislavleva, ME Kotanchek Genetic Programming Theory and Practice VIII, 147-160, 2011 | 14 | 2011 |
| Evolutionary optimization of flavors K Veeramachaneni, K Vladislavleva, M Burland, J Parcon, UM O'Reilly Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 14 | 2010 |
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