[22]

Damiano Azzolini and Fabrizio Riguzzi.
Inference in probabilistic answer set programming under the credal
semantics.
In Roberto Basili, Domenico Lembo, Carla Limongelli, and Andrea
Orlandini, editors, AixIA 2023  Advances in Artificial Intelligence,
Lecture Notes in Artificial Intelligence, Heidelberg, Germany, 2023.
Springer.
To appear.
[ bib ]

[21]

Elisabetta Gentili, Alice Bizzarri, Damiano Azzolini, Riccardo Zese, and
Fabrizio Riguzzi.
Regularization in probabilistic inductive logic programming.
In International Conference on Inductive Logic Programming,
2023.
To appear.
[ bib ]

[20]

Damiano Azzolini and Fabrizio Riguzzi.
Lifted inference for statistical statements in probabilistic answer
set programming.
International Journal of Approximate Reasoning, 2023.
To appear.
[ bib ]

[19]

Tom Schrijvers, Birthe Van Den Berg, and Fabrizio Riguzzi.
Automatic differentiation in prolog.
Theory and Practice of Logic Programming, 23(4):900–917,
2023.
[ bib 
DOI 
.pdf ]

[18]

Damiano Azzolini, Elisabetta Gentili, and Fabrizio Riguzzi.
Link prediction in knowledge graphs with probabilistic logic
programming: Work in progress.
In Joaquín Arias, Sotiris Batsakis, Wolfgang Faber, Gopal Gupta,
Francesco Pacenza, Emmanuel Papadakis, Livio Robaldo, Kilian Ruckschloss,
Elmer Salazar, Zeynep G. Saribatur, Ilias Tachmazidis, Felix Weitkamper, and
Adam Wyner, editors, Proceedings of the International Conference on
Logic Programming 2023 Workshops colocated with the 39th International
Conference on Logic Programming (ICLP 2023), volume 3437 of CEUR
Workshop Proceedings, pages 14. CEURWS.org, 2023.
[ bib 
.pdf ]

[17]

Damiano Azzolini, Elena Bellodi, and Fabrizio Riguzzi.
MAP inference in probabilistic answer set programs.
In Agostino Dovier, Angelo Montanari, and Andrea Orlandini, editors,
AIxIA 2022  Advances in Artificial Intelligence, pages 413426,
Cham, 2023. Springer International Publishing.
[ bib 
DOI 
http ]

[16]

Damiano Azzolini, Elena Bellodi, and Fabrizio Riguzzi.
Approximate inference in probabilistic answer set programming for
statistical probabilities.
In Agostino Dovier, Angelo Montanari, and Andrea Orlandini, editors,
AIxIA 2022  Advances in Artificial Intelligence, pages 3346, Cham,
2023. Springer International Publishing.
[ bib 
DOI 
http ]

[15]

Salvatore Greco, Alessandro Salatiello, Nicolò Fabbri, Fabrizio Riguzzi,
Emanuele Locorotondo, Riccardo Spaggiari, Alfredo De Giorgi, and Angelina
Passaro.
Rapid assessment of COVID19 mortality risk with GASS
classifiers.
Biomedicines, 11(3), 2023.
[ bib 
DOI 
http ]

[14]

Fabrizio Riguzzi and Mariia Mykhailova.
Quantum algorithms for WMC, MPE and MAP.
Available at SSRN.
[ bib 
http ]

[13]

Damiano Azzolini, Elena Bellodi, and Fabrizio Riguzzi.
Abduction in (probabilistic) answer set programming.
In Roberta Calegari, Giovanni Ciatto, and Andrea Omicini, editors,
Proceedings of the 36th Italian Conference on Computational Logic,
volume 3204 of CEUR Workshop Proceedings, pages 90103, Aachen,
Germany, 2022. Sun SITE Central Europe.
[ bib 
.pdf ]

[12]

Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
Semantics for hybrid probabilistic logic programs with function
symbols: Technical summary.
In Joaquín Arias, Roberta Calegari, Luke Dickens, Wolfgang Faber,
Jorge Fandinno, Gopal Gupta, Markus Hecher, Daniela Inclezan, Emily LeBlanc,
Michael Morak, Elmer Salazar, and Jessica Zangari, editors, Proceedings
of the International Conference on Logic Programming 2022 Workshops
colocated with the 38th International Conference on Logic Programming (ICLP
2022), volume 3193 of CEUR Workshop Proceedings, pages 15, Aachen,
Germany, 2022. Sun SITE Central Europe.
[ bib 
.pdf ]

[11]

Damiano Azzolini, Elena Bellodi, and Fabrizio Riguzzi.
Statistical statements in probabilistic logic programming.
In Georg Gottlob, Daniela Inclezan, and Marco Maratea, editors,
Logic Programming and Nonmonotonic Reasoning, pages 4355, Cham, 2022.
Springer International Publishing.
[ bib 
DOI 
http 
.pdf ]

[10]

Marco Alberti, Riccardo Zese, Fabrizio Riguzzi, and Evelina Lamma.
An Iterative Fixpoint Semantics for MKNF Hybrid Knowledge Bases with
Function Symbols.
In Yuliya Lierler, Jose F. Morales, Carmine Dodaro, Veronica Dahl,
Martin Gebser, and Tuncay Tekle, editors, Proceedings of the 38th
International Conference on Logic Programming (Technical Communications),
volume 364 of Electronic Proceedings in Theoretical Computer Science,
pages 6578, Waterloo, Australia, 2022. Open Publishing Association.
[ bib 
DOI 
http 
.pdf ]

[9]

Damiano Azzolini, Elena Bellodi, Stefano Ferilli, Fabrizio Riguzzi, and
Riccardo Zese.
Abduction in probabilistic logic programs.
In Yuliya Lierler, Jose F. Morales, Carmine Dodaro, Veronica Dahl,
Martin Gebser, and Tuncay Tekle, editors, Proceedings of the 38th
International Conference on Logic Programming (Technical Communications),
Recently Published Research track, volume 364 of Electronic Proceedings
in Theoretical Computer Science, pages 174176, Waterloo, Australia, 2022.
Open Publishing Association.
[ bib 
DOI 
http ]

[8]

Michele Fraccaroli, Fabrizio Riguzzi, and Evelina Lamma.
Exploiting parameters learning for hyperparameters optimization in
deep neural networks.
In Yuliya Lierler, Jose F. Morales, Carmine Dodaro, Veronica Dahl,
Martin Gebser, and Tuncay Tekle, editors, Proceedings of the 38th
International Conference on Logic Programming (Technical Communications),
Recently Published Research track, volume 364 of Electronic Proceedings
in Theoretical Computer Science, pages 142144, Waterloo, Australia, 2022.
Open Publishing Association.
[ bib 
DOI 
http ]

[7]

Alessandro Rocchi, Andrea Chiozzi, Marco Nale, Zeljana Nikolic, Fabrizio
Riguzzi, Luana Mantovan, Alessandro Gilli, and Elena Benvenuti.
A machine learning framework for multihazard risk assessment at the
regional scale in earthquake and floodprone areas.
Applied Sciences, 12(2), 2022.
[ bib 
DOI 
http ]

[6]

Damiano Azzolini, Elena Bellodi, Stefano Ferilli, Fabrizio Riguzzi, and
Riccardo Zese.
Abduction with probabilistic logic programming under the distribution
semantics.
International Journal of Approximate Reasoning, 142:4163,
2022.
[ bib 
DOI 
http ]

[5]

Michele Fraccaroli, Evelina Lamma, and Fabrizio Riguzzi.
Symbolic DNNTuner: A Python and ProbLogbased system for
optimizing deep neural networks hyperparameters.
SoftwareX, 17:100957, 2022.
[ bib 
DOI 
http ]

[4]

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini,
Giovanni Bechini, Giuseppe Cota, and Fabrizio Riguzzi.
Prediction of gas turbine trip: A novel methodology based on random
forest models.
Journal of Engineering for Gas Turbines and Power, 144(3),
2022.
GTP211324.
[ bib 
DOI ]

[3]

Damiano Azzolini, Fabrizio Riguzzi, Elena Bellodi, and Evelina Lamma.
A probabilistic logic model of lightning network.
In Witold Abramowicz, Sören Auer, and Milena Stróżyna,
editors, Business Information Systems Workshops, Lecture Notes in
Business Information Processing (LNBIP), pages 321333, Cham, Switzerland,
2022. Springer International Publishing.
[ bib 
DOI 
http 
.pdf ]

[2]

Riccardo Zese, Elena Bellodi, Michele Fraccaroli, Fabrizio Riguzzi, and Evelina
Lamma.
Neural networks and deep learning fundamentals.
In Rino Micheloni and Cristian Zambelli, editors, Machine
Learning and Nonvolatile Memories, pages 2342. Springer International
Publishing, Cham, 2022.
[ bib 
DOI 
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[1]

Damiano Azzolini and Fabrizio Riguzzi.
Probabilistic logic models for the lightning network.
Cryptography, 6(2), 2022.
[ bib 
DOI 
http 
http ]
