| Stacked structure learning for lifted relational neural networks G Šourek, M Svatoš, F Železný, S Schockaert, O Kuželka Inductive Logic Programming: 27th International Conference, ILP 2017 …, 2018 | 13 | 2018 |
| Recursive polynomial reductions for classical planning J Tozicka, J Jakubuv, M Svatos, A Komenda Proceedings of the International Conference on Automated Planning and …, 2016 | 8 | 2016 |
| STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment M Svatoš, S Schockaert, J Davis, O Kuzelka | 8* | |
| Pruning hypothesis spaces using learned domain theories M Svatoš, G Šourek, F Železný, S Schockaert, O Kuželka Inductive Logic Programming: 27th International Conference, ILP 2017 …, 2018 | 5 | 2018 |
| On Discovering Interesting Combinatorial Integer Sequences M Svatoš, P Jung, J Tóth, Y Wang, O Kuželka arXiv preprint arXiv:2302.04606, 2023 | 3 | 2023 |
| Learning to Generate Molecules From Small Datasets Using Neural Markov Logic Networks M Svatoš, P Jung, F Železný, G Marra, O Kuželka Inductive Logic Programming: Late-Breaking Papers, 2022, 2022 | 1 | 2022 |
| Cautious Rule-Based Collective Inference M Svatoš Proceedings of the 28th International Joint Conference on Artificial …, 2019 | | 2019 |
| Structure learning of neural-symbolic architectures M Svatoš Czech Technical University in Prague, 2016 | | 2016 |
