| Deepproblog: Neural probabilistic logic programming R Manhaeve, S Dumancic, A Kimmig, T Demeester, L De Raedt Advances in neural information processing systems 31, 2018 | 917 | 2018 |
| Learning sequence encoders for temporal knowledge graph completion A García-Durán, S Dumančić, M Niepert arXiv preprint arXiv:1809.03202, 2018 | 709 | 2018 |
| From statistical relational to neurosymbolic artificial intelligence: A survey G Marra, S Dumančić, R Manhaeve, L De Raedt Artificial Intelligence 328, 104062, 2024 | 348* | 2024 |
| Neural probabilistic logic programming in DeepProbLog R Manhaeve, S Dumančić, A Kimmig, T Demeester, L De Raedt Artificial Intelligence 298, 103504, 2021 | 233 | 2021 |
| Inductive logic programming at 30: a new introduction A Cropper, S Dumančić Journal of Artificial Intelligence Research 74, 765-850, 2022 | 195 | 2022 |
| Inductive logic programming at 30 A Cropper, S Dumančić, R Evans, SH Muggleton Machine Learning 111 (1), 147-172, 2022 | 131 | 2022 |
| Turning 30: New ideas in inductive logic programming A Cropper, S Dumančić, SH Muggleton arXiv preprint arXiv:2002.11002, 2020 | 125 | 2020 |
| Neuro-Symbolic= Neural+ Logical+ Probabilistic. L De Raedt, R Manhaeve, S Dumancic, T Demeester, A Kimmig NeSy@ IJCAI, 2019 | 104 | 2019 |
| Cobra: A fast and simple method for active clustering with pairwise constraints T Van Craenendonck, S Dumancic, H Blockeel arXiv preprint arXiv:1801.09955, 2018 | 45 | 2018 |
| Cobras: Interactive clustering with pairwise queries T Van Craenendonck, S Dumančić, E Van Wolputte, H Blockeel International Symposium on Intelligent Data Analysis, 353-366, 2018 | 42* | 2018 |
| Learning Relational Representations with Auto-encoding Logic Programs S Dumancic, T Guns, W Meert, H Blockeel International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019 | 40* | 2019 |
| Learning large logic programs by going beyond entailment A Cropper, S Dumančić arXiv preprint arXiv:2004.09855, 2020 | 34 | 2020 |
| COBRASTS: A New Approach to Semi-supervised Clustering of Time Series T Van Craenendonck, W Meert, S Dumančić, H Blockeel International conference on discovery science, 179-193, 2018 | 28 | 2018 |
| Knowledge Refactoring for Inductive Program Synthesis S Dumancic, T Guns, A Cropper AAAI Conference on Artificial Intelligence 35, 7271--7278, 2021 | 24* | 2021 |
| Clustering-based relational unsupervised representation learning with an explicit distributed representation S Dumancic, H Blockeel International Joint Conference on Artificial Intelligence (IJCAI) 2017, 2017 | 21 | 2017 |
| Neuro-symbolic AI= neural+ logical+ probabilistic AI P Hitzler, M Sarker Neuro-Symbolic Artificial Intelligence: The State of the Art 342, 173, 2022 | 18 | 2022 |
| A comparative study of distributional and symbolic paradigms for relational learning S Dumancic, A García-Durán, M Niepert arXiv preprint arXiv:1806.11391, 2018 | 17* | 2018 |
| An expressive dissimilarity measure for relational clustering using neighbourhood trees S Dumančić, H Blockeel Machine learning 106 (9), 1523-1545, 2017 | 13* | 2017 |
| Feature interactions in xgboost K Goyal, S Dumancic, H Blockeel arXiv preprint arXiv:2007.05758, 2020 | 12 | 2020 |
| DeepProbLog: Integrating logic and learning through algebraic model counting R Manhaeve, L De Raedt, A Kimmig, S Dumancic, T Demeester KR2ML Workshop@ Neurips' 19, Location: Vancouver, Canada, 2019 | 9 | 2019 |
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro UniversityVerified email at cs.kuleuven.be
