Advanced SMT techniques for weighted model integration P Morettin, A Passerini, R Sebastiani Artificial Intelligence 275, 1-27, 2019 | 33 | 2019 |

Efficient weighted model integration via smt-based predicate abstraction P Morettin, A Passerini, R Sebastiani def 1 (x1), x2, 2017 | 32 | 2017 |

Efficient generation of structured objects with constrained adversarial networks L Di Liello, P Ardino, J Gobbi, P Morettin, S Teso, A Passerini Advances in neural information processing systems 33, 14663-14674, 2020 | 25 | 2020 |

TN-Grid and gene@ home project: Volunteer Computing for Bioinformatics F Asnicar, N Sella, L Masera, P Morettin, T Tolio, S Semeniuta, C Moser, ... CEUR WORKSHOP PROCEEDINGS, 1-15, 2015 | 18 | 2015 |

Learning weighted model integration distributions P Morettin, S Kolb, S Teso, A Passerini Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5224-5231, 2020 | 14 | 2020 |

The pywmi framework and toolbox for probabilistic inference using weighted model integration S Kolb, P Morettin, P Zuidberg Dos Martires, F Sommavilla, A Passerini, ... Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 13 | 2019 |

NES^{2}RA: Network expansion by stratified variable subsetting and ranking aggregationF Asnicar, L Masera, E Coller, C Gallo, N Sella, T Tolio, P Morettin, ... The International Journal of High Performance Computing Applications 32 (3 …, 2018 | 12 | 2018 |

Probabilistic inference with algebraic constraints: Theoretical limits and practical approximations Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck Advances in Neural Information Processing Systems 33, 11564-11575, 2020 | 11 | 2020 |

Hybrid probabilistic inference with logical and algebraic constraints: a survey P Morettin, P Zuidberg Dos Martires, S Kolb, A Passerini IJCAI, 4533-4542, 2021 | 10 | 2021 |

Discovering candidates for gene network expansion by distributed volunteer computing F Asnicar, L Erculiani, F Galante, C Gallo, L Masera, P Morettin, N Sella, ... 2015 IEEE Trustcom/BigDataSE/ISPA 3, 248-253, 2015 | 10 | 2015 |

SMT-based weighted model integration with structure awareness G Spallitta, G Masina, P Morettin, A Passerini, R Sebastiani Uncertainty in Artificial Intelligence, 1876-1885, 2022 | 8 | 2022 |

Scaling up hybrid probabilistic inference with logical and arithmetic constraints via message passing Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck International Conference on Machine Learning, 10990-11000, 2020 | 8 | 2020 |

Zuidberg Dos Martires S Kolb, P Morettin P., Sommavilla, F., Passerini, A., Sebastiani, R., and De Raedt, L. The …, 2019 | 6 | 2019 |

Is Parameter Learning via Weighted Model Integration Tractable? Z Zeng, P Morettin, F Yan, A Passerini, G Van den Broeck The 4th Workshop on Tractable Probabilistic Modeling, 2021 | 3 | 2021 |

Efficient generation of structured objects with Constrained Adversarial Networks J Gobbi, L Di Liello, P Ardino, P Morettin, S Teso, A Passerini | 3 | 2019 |

Enhancing SMT-based Weighted Model Integration by structure awareness G Spallitta, G Masina, P Morettin, A Passerini, R Sebastiani Artificial Intelligence 328, 104067, 2024 | 1 | 2024 |

Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing Z Zeng, F Yan, P Morettin, A Vergari, GV Broeck arXiv preprint arXiv:1909.09362, 2019 | 1 | 2019 |

A Unified Framework for Probabilistic Verification of AI Systems via Weighted Model Integration P Morettin, A Passerini, R Sebastiani arXiv preprint arXiv:2402.04892, 2024 | | 2024 |

Top-Down Knowledge Compilation for Counting Modulo Theories V Derkinderen, PZD Martires, S Kolb, P Morettin arXiv preprint arXiv:2306.04541, 2023 | | 2023 |

Semantic Loss Functions for Neuro-Symbolic Structured Prediction K Ahmed, S Teso, P Morettin, L Di Liello, P Ardino, J Gobbi, Y Liang, ... Compendium of Neurosymbolic Artificial Intelligence, 485-505, 2023 | | 2023 |