Probabilistic Logic Programming in Action. - Arnaud Nguembang Fadja; Fabrizio Riguzzi (BIRS-IMLKE, 2015)

Deep Probabilistic Logic Programming. - Arnaud Nguembang Fadja; Evelina Lamma; Fabrizio Riguzzi (PLP@ILP, 2017)

Deep Learning for Probabilistic Logic Programming. - Arnaud Nguembang Fadja (DC@AI*IA, 2018)

Vision Inspection with Neural Networks. - Arnaud Nguembang Fadja; Evelina Lamma; Fabrizio Riguzzi (RiCeRcA@AI*IA, 2018)

Expectation Maximization in Deep Probabilistic Logic Programming. - Arnaud Nguembang Fadja; Fabrizio Riguzzi; Evelina Lamma (AI*IA, 2018)

Learning the Parameters of Deep Probabilistic Logic Programs. - Arnaud Nguembang Fadja; Fabrizio Riguzzi; Evelina Lamma (PLP@ILP, 2018)

Lifted discriminative learning of probabilistic logic programs. - Arnaud Nguembang Fadja; Fabrizio Riguzzi (Mach. Learn., 2019)

Identification of natural selection in genomic data with deep convolutional neural network. - Arnaud Nguembang Fadja; Fabrizio Riguzzi; Giorgio Bertorelle; Emiliano Trucchi (BioData Min., 2021)

Learning hierarchical probabilistic logic programs. - Arnaud Nguembang Fadja; Fabrizio Riguzzi; Evelina Lamma (Mach. Learn., 2021)

Neural-Symbolic Ensemble Learning for early-stage prediction of critical state of Covid-19 patients. - Arnaud Nguembang Fadja; Michele Fraccaroli; Alice Bizzarri; Giulia Mazzuchelli; Evelina Lamma (Medical Biol. Eng. Comput., 2022)

Label Assisted Autoencoder for Anomaly Detection in Power Generation Plants. - Marcellin Atemkeng; Victor Osanyindoro; Rockefeller Rockefeller; Sisipho Hamlomo; Jecinta Mulongo; Theophilus Ansah-Narh; Franklin Tchakounté; Arnaud Nguembang Fadja (CoRR, 2023)

Ensemble learning and deep learning-based defect detection in power generation plants. - Marcellin Atemkeng; Victor Osanyindoro; Rockefeller Rockefeller; Sisipho Hamlomo; Jecinta Mulongo; Theophilus Ansah-Narh; Franklin Tchakounté; Arnaud Nguembang Fadja (J. Intell. Syst., 2024)