Dr Arnaud Nguembang Fadja

Publications

Revues internationales

1.     2024    . Arnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi, Fabrizio Riguzzi, Enzo Losi, Lucrezia Manservigi, Mauro Venturini and Giovanni Bechini Machine Learning Approaches for the Prediction of Gas Turbine Transients. Journal of Computer Science, 20(5), 495-510. https://doi.org/10.3844/jcssp.2024.495.510 [.pdf]
  
2.     2023    Arnaud Nguembang Fadja, Avuya Deyi, Eleonora Deborah Goosen, Xavier Siwe Noundou, and Marcellin Atemkeng. Dataset of Selected Medicinal Plant Species of the Genus Brachylaena: A Comparative Application of Deep Learning Models for Plant Leaf Recognition. [.pdf]
  
3.     2022    Arnaud Nguembang Fadja, Michele Fraccaroli, and Alice Bizzarri. Neural-Symbolic System for Predicting COVID-19 Positivity. Clinical Case Reports International [.pdf]
  
4.     2022    Arnaud Nguembang Fadja, Evelina Lamma, Michele Fraccaroli, Alice Bizzarri, and Giulia Mazzuchelli. Neural-Symbolic Ensemble Learning for early-stage prediction of Critical State of Covid-19 patients. Med Biol Eng Comput (2022). https://doi.org/10.1007/s11517-022-02674-1 [.pdf]
  
5.     2021    Arnaud Nguembang Fadja, Fabrizio Riguzzi, Giorgio Bertorelle, and Emiliano Trucchi. Identification of natural selection in genomic data with deep convolutional neural network. BioData Mining 14, 51 (2021). https://doi.org/10.1186/s13040-021-00280-9 [.pdf]
  
6.     2021    Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma. Learning hierarchical probabilistic logic programs. Machine Learning, © Springer, 2021 [.pdf]
  
7.     2019    Arnaud Nguembang Fadja, and Fabrizio Riguzzi. Lifted discriminative learning of probabilistic logic programs. Machine Learning, 108(7):1111--1135, © Springer, 2019. The original publication is available at http://link.springer.com [.pdf]

Chapitres de livres

1.     2022    Arnaud Nguembang Fadja, and Fabrizio Riguzzi. Scalable Probabilistic Inductive Logic Programming for Big Data. PhD. thesis [.pdf]
  
2.     2017    Arnaud Nguembang Fadja, and Fabrizio Riguzzi. Probabilistic logic programming in action. In Andreas Holzinger, Randy Goebel, Massimo Ferri, and Vasile Palade, editors, Towards Integrative Machine Learning and Knowledge Extraction: BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers, volume 10344 of Lecture Notes in Computer Science, pages 89--116. Springer, Heidelberg, Germany, © Springer, 2017. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-69775-8_5. [.pdf]

Conférences internationales

1.     2023    Arnaud Nguembang Fadja, and Sain Rigobert Che. Intelligent Fruit Inspection System: Developing a YOLO-based Model for Identifying Defects on Plums Surface. DeepLearningIndaba 2023 Conference [.pdf]
  
2.     2018    Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma. Expectation maximization in deep probabilistic logic programming.. In Chiara Ghidini, Bernardo Magnini, and Andrea Passerini, editors, Proceedings of the 17th Conference of the Italian Association for Artificial Intelligence (AI*IA2018), Trento, Italy, 20-23 November, 2018, volume 11298 of Lecture Notes in Computer Science, pages 293--306, Heidelberg, Germany, 2018. © Springer, Springer. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-03840-3_22. [.pdf]
  
3.     2017    Arnaud Nguembang Fadja, and Fabrizio Riguzzi. Lifted discriminative learning of probabilistic logic programs.. In Nicolas Lachiche and Christel Vrain, editors, 27th International Conference on Inductive Logic Programming, ILP 2017, 2017. [.pdf]

Workshops internationaux

1.     2018    Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma. Learning the parameters of deep probabilistic logic programs.. In Elena Bellodi and Tom Schrijvers, editors, Probabilistic Logic Programming (PLP 2018), volume 2219 of CEUR Workshop Proceedings, pages 9--14, Aachen, Germany, 2018. © by the authors, Sun SITE Central Europe. [.pdf]
  
2.     2018    Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma. Vision inspection with neural networks. In Marco Maratea and Mauro Vallati, editors, R.i.C.e.R.c.A: RCRA Incontri E Confronti, Proceedings of the RiCeRcA Workshop co-located with the 17th International Conference of the Italian Association for Artificial Intelligence (Ai*iA 2018), volume 2272 of CEUR Workshop Proceedings, pages 1--10, Aachen, Germany, 2018. © by the authors, Sun SITE Central Europe. [.pdf]
  
3.     2018    Arnaud Nguembang Fadja, and Fabrizio Riguzzi. Deep learning for probabilistic logic programming. In Marco Rospocher, Luciano Serafini, and Sara Tonelli, editors, AI*IA 2018 Doctoral Consortium, Proceedings of the AI*IA Doctoral Consortium (DC), volume 2249 of CEUR Workshop Proceedings, pages 43--47, Aachen, Germany, 2018. © by the authors, Sun SITE Central Europe. [.pdf]
  
4.     2017    Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma. Deep probabilistic logic programming. In Christian Theil Have and Riccardo Zese, editors, Proceedings of the 4th International Workshop on Probabilistic logic programming, (PLP 2017), volume 1916 of CEUR Workshop Proceedings, pages 3--14, Aachen, Germany, 2017. Sun SITE Central Europe. [.pdf]