Lifted relational neural networks: Efficient learning of latent relational structures G Sourek, V Aschenbrenner, F Zelezny, S Schockaert, O Kuzelka Journal of Artificial Intelligence Research 62, 69-100, 2018 | 149 | 2018 |
Exploiting sports-betting market using machine learning O Hubáček, G Šourek, F Železný International Journal of Forecasting 35 (2), 783-796, 2019 | 76 | 2019 |
Learning to predict soccer results from relational data with gradient boosted trees O Hubáček, G Šourek, F Železný Machine Learning 108, 29-47, 2019 | 71 | 2019 |
Lifted relational neural networks G Šourek, V Aschenbrenner, F Zelezný, O Kuzelka Proceedings of the NIPS Workshop on Cognitive Computation: Integrating …, 2015 | 31 | 2015 |
Learning predictive categories using lifted relational neural networks G Šourek, S Manandhar, F Železný, S Schockaert, O Kuželka Inductive Logic Programming: 26th International Conference, ILP 2016, London …, 2017 | 18 | 2017 |
Beyond graph neural networks with lifted relational neural networks G Šourek, F Železný, O Kuželka Machine Learning 110 (7), 1695-1738, 2021 | 16 | 2021 |
Lossless compression of structured convolutional models via lifting G Sourek, F Zelezny, O Kuzelka arXiv preprint arXiv:2007.06567, 2020 | 16 | 2020 |
Deep learning from spatial relations for soccer pass prediction O Hubáček, G Šourek, F Železný Machine Learning and Data Mining for Sports Analytics: 5th International …, 2019 | 13 | 2019 |
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 |
Forty years of score-based soccer match outcome prediction: an experimental review O Hubáček, G Šourek, F Železný IMA Journal of Management Mathematics 33 (1), 1-18, 2022 | 10 | 2022 |
Optimal sports betting strategies in practice: an experimental review U Matej, Š Gustav, H Ondřej, Ž Filip IMA Journal of Management Mathematics 32 (4), 465-489, 2021 | 10 | 2021 |
Score-based soccer match outcome modeling–an experimental review O Hubácek, G Sourek, F Zelezny MathSport International, 2019 | 9 | 2019 |
Predicting top-k trends on twitter using graphlets and time features G Šourek, O Kuzelka, F Zelezný ILP 2013 Late Breaking Papers, 52, 2013 | 8 | 2013 |
Beating the market with a bad predictive model O Hubáček, G Šír International Journal of Forecasting 39 (2), 691-719, 2023 | 7 | 2023 |
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 |
Events from network flows G Sourek, K Bartos, F Zelezny, T Pevny, P Somol US Patent 9,374,383, 2016 | 5 | 2016 |
Efficient extraction of network event types from NetFlows G Sourek, F Zelezny Security and Communication Networks 2019, 2019 | 4 | 2019 |
Learning to detect network intrusion from a few labeled events and background traffic G Šourek, O Kuželka, F Železný Intelligent Mechanisms for Network Configuration and Security: 9th IFIP WG 6 …, 2015 | 3 | 2015 |
A deep learning blueprint for relational databases L Zahradník, J Neumann, G Šír NeurIPS 2023 Second Table Representation Learning Workshop, 2023 | 2 | 2023 |
Learning with Molecules beyond Graph Neural Networks G Sourek, F Zelezny, O Kuzelka arXiv preprint arXiv:2011.03488, 2020 | 2 | 2020 |