Paolo Morettin
Paolo Morettin
Post-doctoral researcher, KU Leuven
Verified email at kuleuven.be
Title
Cited by
Cited by
Year
Efficient weighted model integration via smt-based predicate abstraction
P Morettin, A Passerini, R Sebastiani
Proceedings of the 26th International Joint Conference on Artificial …, 2017
232017
Advanced SMT techniques for weighted model integration
P Morettin, A Passerini, R Sebastiani
Artificial Intelligence 275, 1-27, 2019
152019
TN-grid and gene@ home project: volunteer computing for bioinformatics
F Asnicar, N Sella, L Masera, P Morettin, T Tolio, S Semeniuta, C Moser, ...
BOINC: FAST 2015 International Conference BOINC: FAST 2015Second …, 2015
132015
NES2RA: Network expansion by stratified variable subsetting and ranking aggregation
F Asnicar, L Masera, E Coller, C Gallo, N Sella, T Tolio, P Morettin, ...
The International Journal of High Performance Computing Applications 32 (3 …, 2018
112018
The pywmi framework and toolbox for probabilistic inference using weighted model integration
S Kolb, P Morettin, P Zuidberg Dos Martires, F Sommavilla, A Passerini, ...
https://www. ijcai. org/proceedings/2019/, 2019
82019
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
82015
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
72020
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, 2020
72020
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
52020
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, 2020
22020
Hybrid probabilistic inference with logical and algebraic constraints: a survey
P Morettin, P Zuidberg Dos Martires, S Kolb, A Passerini
Proceedings of the 30th International Joint Conference on Artificial …, 2021
12021
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
12019
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
2021
Efficient generation of structured objects with Constrained Adversarial Networks
J Gobbi, L Di Liello, P Ardino, P Morettin, S Teso, A Passerini
2019
Co-creating Platformer Levels with Constrained Adversarial Networks
P MORETTIN, A PASSERINI, S TESO
2018
Discovering candidates for gene network expansion by variable subsetting and ranking aggregation
L Erculiani, F Galante, C Gallo, F Asnicar, L Masera, P Morettin, N Sella, ...
Network Biology Community-ISMB meeting (NetBio _SIG_2015), 2015
2015
Probabilistic Inference with Algebraic Constraints
Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck
Supplementary Material for Efficient Generation of Structured Objects with Constrained Adversarial Networks
L Di Liello, P Ardino, J Gobbi, P Morettin, S Teso, A Passerini
Relax, compensate and then integrate
Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck
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Articles 1–19