| Evolving non-linear stacking ensembles for prediction of go player attributes J Moudrík, R Neruda 2015 IEEE symposium series on computational intelligence, 1673-1680, 2015 | 11 | 2015 |
| Evaluating go game records for prediction of player attributes J Moudŕík, P Baudiš, R Neruda 2015 IEEE Conference on Computational Intelligence and Games (CIG), 162-168, 2015 | 8 | 2015 |
| Combining top-down and bottom-up approaches for automated discovery of typed programs T Kren, J Moudřík, R Neruda 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2017 | 4 | 2017 |
| Determining player skill in the game of go with deep neural networks J Moudřík, R Neruda Theory and Practice of Natural Computing: 5th International Conference, TPNC …, 2016 | 4 | 2016 |
| Meta-learning methods for analyzing go playing trends J Moudřík Univerzita Karlova, Matematicko-fyzikální fakulta, 2013 | 4 | 2013 |
| On move pattern trends in a large go games corpus P Baudiš, J Moudřík arXiv preprint arXiv:1209.5251, 2012 | 4 | 2012 |
| Algorithm Discovery with Monte-Carlo Search: Controlling the Size J Moudřík, T Křen, R Neruda 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 2 | 2017 |
| Unsupervised and Supervised Activity Analysis of Drone Sensor Data R Neruda, M Pilát, J Moudřík Applied Computer Sciences in Engineering: 4th Workshop on Engineering …, 2017 | 1 | 2017 |
| Style consensus: Style of professional players, judged by strong players J Moudrık, P Baudiš Tech. Rep., May 2013.[Online]. Available: http://gostyle. j2m. cz/FILES …, 2013 | 1 | 2013 |
| Deep Learning in Go-Overview J Moudřík | | |
Roman NerudaResearcher at Institute of Computer Science, Czech Academy of SciencesVerified email at cs.cas.cz
