| From Statistical Relational to Neurosymbolic Artificial Intelligence L De Raedt, S Dumančić, R Manhaeve, G Marra Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 181 | 2020 |
| Concept embedding models: Beyond the accuracy-explainability trade-off M Espinosa Zarlenga, P Barbiero, G Ciravegna, G Marra, F Giannini, ... Advances in Neural Information Processing Systems 35, 21400-21413, 2022 | 117* | 2022 |
| Integrating learning and reasoning with deep logic models G Marra, F Giannini, M Diligenti, M Gori European Conference on Machine Learning and Principles and Practice of …, 2019 | 68 | 2019 |
| Deepstochlog: Neural stochastic logic programming T Winters, G Marra, R Manhaeve, L De Raedt AAAI, 2022 | 65 | 2022 |
| LYRICS: a General Interface Layer to Integrate Logic Inference and Deep Learning⋆ G Marra, F Giannini, M Diligenti, M Gori European Conference on Machine Learning and Principles and Practice of …, 2019 | 63* | 2019 |
| Relational Neural Machines G Marra, M Diligenti, F Giannini, M Gori, M Maggini ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 …, 2020 | 56 | 2020 |
| Neural markov logic networks G Marra, O Kuželka UAI, 2021 | 55 | 2021 |
| Interpretable neural-symbolic concept reasoning P Barbiero, G Ciravegna, F Giannini, ME Zarlenga, Magister, L Charlotte, ... International Conference on Machine Learning, 2023 | 27* | 2023 |
| Approximate Inference for Neural Probabilistic Logic Programming. R Manhaeve, G Marra, L De Raedt KR, 475-486, 2021 | 27 | 2021 |
| From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey G Marra, S Dumančić, R Manhaeve, L De Raedt Artificial Intelligence 2024, 2024 | 26 | 2024 |
| Deep constraint-based propagation in graph neural networks M Tiezzi, G Marra, S Melacci, M Maggini IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2), 727-739, 2021 | 24* | 2021 |
| Safe Reinforcement Learning via Probabilistic Logic Shields WC Yang, G Marra, G Rens, L De Raedt IJCAI, 2023 | 20 | 2023 |
| T-norms driven loss functions for machine learning F Giannini, M Diligenti, M Maggini, M Gori, G Marra Applied Intelligence 53 (15), 18775-18789, 2023 | 19* | 2023 |
| Vael: Bridging variational autoencoders and probabilistic logic programming E Misino, G Marra, E Sansone Advances in Neural Information Processing Systems 35, 4667-4679, 2022 | 17 | 2022 |
| Temperature sensing characteristics and long term stability of power LEDs used for voltage vs. Junction temperature measurements and related procedure FG Della Corte, G Pangallo, R Carotenuto, D Iero, G Marra, M Merenda, ... IEEE access 8, 43057-43066, 2020 | 17 | 2020 |
| Online Learning of Non-Markovian Reward Models G Rens, JF Raskin, R Reynouad, G Marra ICART, 2020 | 17 | 2020 |
| An unsupervised character-aware neural approach to word and context representation learning G Marra, A Zugarini, S Melacci, M Maggini Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 17 | 2018 |
| Local propagation in constraint-based neural network G Marra, M Tiezzi, S Melacci, A Betti, M Maggini, M Gori IJCNN 2020, 2020 | 15 | 2020 |
| Learning in text streams: Discovery and disambiguation of entity and relation instances M Maggini, G Marra, S Melacci, A Zugarini IEEE Transactions on Neural Networks and Learning Systems 31 (11), 4475-4486, 2019 | 14 | 2019 |
| Constraint-based visual generation G Marra, F Giannini, M Diligenti, M Gori Artificial Neural Networks and Machine Learning–ICANN 2019: Image Processing …, 2019 | 14 | 2019 |
