Federico Succetti

According to our database, Federico Succetti authored at least 10 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Advancements in time series analysis using deep learning.

Federico Succetti

PhD thesis, 2025

Multi-label classification with imbalanced classes by fuzzy deep neural networks.

Federico Succetti, Antonello Rosato, Massimo Panella

Integr. Comput. Aided Eng., 2025

Machine Learning for Fluid Thermodynamics: State of the Art and Open Challenges.

Federico Succetti, Massimo Panella, Paolo Giannitrapani, Jean-Christophe Rigo, Stefania Colonnese

IEEE Access, 2025

2024

A Neural Network Symbolic Approach to Structural Health Monitoring in Aerospace Applications.

Federica Angeletti, Federico Succetti, Massimo Panella, Antonello Rosato

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

An adaptive embedding procedure for time series forecasting with deep neural networks.

Federico Succetti, Antonello Rosato, Massimo Panella

Neural Networks, October, 2023

2022

Nonexclusive Classification of Household Appliances by Fuzzy Deep Neural Networks.

Federico Succetti, Antonello Rosato, Massimo Panella

AII, 2022

2021

Time Series Prediction with Autoencoding LSTM Networks.

Federico Succetti, Andrea Ceschini, Francesco Di Luzio, Antonello Rosato, Massimo Panella

Proceedings of the Advances in Computational Intelligence, 2021

A Blockwise Embedding for Multi-Day-Ahead Prediction of Energy Time Series by Randomized Deep Neural Networks.

Francesco Di Luzio, Antonello Rosato, Federico Succetti, Massimo Panella

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Deep Neural Networks for Multivariate Prediction of Photovoltaic Power Time Series.

Federico Succetti, Antonello Rosato, Rodolfo Araneo, Massimo Panella

IEEE Access, 2020

ADMM Consensus for Deep LSTM Networks.

Antonello Rosato, Federico Succetti, Marcello Barbirotta, Massimo Panella

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020