Area of research
Artificial Intelligence · Computational Theory and Mathematics
Research interest
Research interests include Computer science, Artificial intelligence, Artificial neural network, Machine learning, Anomaly detection, and Probabilistic logic.
Detection of Cliff Top Erosion Drivers through Machine Learning Algorithms between Portonovo and Trave Cliffs (Ancona, Italy)
Integration between constrained optimization and deep networks: a survey
Integration of Deep Generative Anomaly Detection Algorithm in High-Speed Industrial Line
Exploiting CNN’s visual explanations to drive anomaly detection
GRD‐Net: Generative‐Reconstructive‐Discriminative Anomaly Detection with Region of Interest Attention Module
Efficient Resource-Aware Neural Architecture Search with a Neuro-Symbolic Approach
A Machine Learning Pipeline to Analyse Multispectral and Hyperspectral Images: Full/Regular Research Paper (CSCI-RTHI)
Symbolic DNN-Tuner: A Python and ProbLog-based system for optimizing Deep Neural Networks hyperparameters
Neural-Symbolic Ensemble Learning for early-stage prediction of critical state of Covid-19 patients
Neural Networks and Deep Learning Fundamentals
Proceedings 38th International Conference on Logic Programming
Machine Learning Techniques for Extracting Relevant Features from Clinical Data for COVID-19 Mortality Prediction
Automatic Setting of DNN Hyper-Parameters by Mixing Bayesian Optimization and Tuning Rules
Automatic Setting of DNN Hyper-Parameters by Mixing Bayesian Optimization and Tuning Rules