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[22]
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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 ]
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[21]
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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 ]
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[20]
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Damiano Azzolini and Fabrizio Riguzzi.
Lifted inference for statistical statements in probabilistic answer
set programming.
International Journal of Approximate Reasoning, 2023.
To appear.
[ bib ]
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[19]
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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 ]
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[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 co-located with the 39th International
Conference on Logic Programming (ICLP 2023), volume 3437 of CEUR
Workshop Proceedings, pages 1--4. CEUR-WS.org, 2023.
[ bib |
.pdf ]
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[17]
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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 413--426,
Cham, 2023. Springer International Publishing.
[ bib |
DOI |
http ]
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[16]
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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 33--46, Cham,
2023. Springer International Publishing.
[ bib |
DOI |
http ]
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[15]
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Salvatore Greco, Alessandro Salatiello, Nicolò Fabbri, Fabrizio Riguzzi,
Emanuele Locorotondo, Riccardo Spaggiari, Alfredo De Giorgi, and Angelina
Passaro.
Rapid assessment of COVID-19 mortality risk with GASS
classifiers.
Biomedicines, 11(3), 2023.
[ bib |
DOI |
http ]
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[14]
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Fabrizio Riguzzi and Mariia Mykhailova.
Quantum algorithms for WMC, MPE and MAP.
Available at SSRN.
[ bib |
http ]
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[13]
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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 90--103, Aachen,
Germany, 2022. Sun SITE Central Europe.
[ bib |
.pdf ]
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[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
co-located with the 38th International Conference on Logic Programming (ICLP
2022), volume 3193 of CEUR Workshop Proceedings, pages 1--5, Aachen,
Germany, 2022. Sun SITE Central Europe.
[ bib |
.pdf ]
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[11]
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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 43--55, Cham, 2022.
Springer International Publishing.
[ bib |
DOI |
http |
.pdf ]
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[10]
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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 65--78, Waterloo, Australia, 2022. Open Publishing Association.
[ bib |
DOI |
http |
.pdf ]
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[9]
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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 174--176, Waterloo, Australia, 2022.
Open Publishing Association.
[ bib |
DOI |
http ]
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[8]
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Michele Fraccaroli, Fabrizio Riguzzi, and Evelina Lamma.
Exploiting parameters learning for hyper-parameters 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 142--144, Waterloo, Australia, 2022.
Open Publishing Association.
[ bib |
DOI |
http ]
|
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[7]
|
Alessandro Rocchi, Andrea Chiozzi, Marco Nale, Zeljana Nikolic, Fabrizio
Riguzzi, Luana Mantovan, Alessandro Gilli, and Elena Benvenuti.
A machine learning framework for multi-hazard risk assessment at the
regional scale in earthquake and flood-prone areas.
Applied Sciences, 12(2), 2022.
[ bib |
DOI |
http ]
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[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, 142:41--63,
2022.
[ bib |
DOI |
http ]
|
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[5]
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Michele Fraccaroli, Evelina Lamma, and Fabrizio Riguzzi.
Symbolic DNN-Tuner: A Python and ProbLog-based system for
optimizing deep neural networks hyperparameters.
SoftwareX, 17:100957, 2022.
[ bib |
DOI |
http ]
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[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.
GTP-21-1324.
[ bib |
DOI ]
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[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 321--333, Cham, Switzerland,
2022. Springer International Publishing.
[ bib |
DOI |
http |
.pdf ]
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[2]
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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 Non-volatile Memories, pages 23--42. 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 |
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