Luca Pedrelli
I received the Master’s degree in Computer Science from the University of Pisa, Pisa, Italy, in 2015. In 2019 I defended my Ph.D. Thesis, regarding deep recurrent neural networks for time-series and sequence analysis, at the Department of Computer Science, University of Pisa.
My research concerns the analysis of language comprehension in human brain through the design and the study of novel hierarchical and deep Neural Network architectures in the field of robot speech recognition.
My research interests include deep learning, machine learning, neural networks, reservoir computing models, data analysis and artificial intelligence.
Scientific articles
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Continuously Deep Recurrent Neural Networks
Lecture Notes in Computer Science. 2024-01-01. : 59-73.
10.1007/978-3-031-70368-3_4 -
ReservoirPy: An Efficient and User-Friendly Library to Design Echo State Networks
Artificial Neural Networks and Machine Learning – ICANN 2020. 2020-01-01. : 494-505.
10.1007/978-3-030-61616-8_40 -
Fast Spectral Radius Initialization for Recurrent Neural Networks
Proceedings of the International Neural Networks Society. 2019-04-03. : 380-390.
10.1007/978-3-030-16841-4_39 -
Design of deep echo state networks
Neural Networks. 2018-12-01. 108 : 33-47.
10.1016/j.neunet.2018.08.002 -
Hierarchical temporal representation in linear reservoir computing
Neural Advances in Processing Nonlinear Dynamic Signals. 2018-07-22. : 119-129.
10.1007/978-3-319-95098-3_11 -
Deep reservoir computing: A critical experimental analysis
Neurocomputing. 2017-12-01. 268 : 87-99.
10.1016/j.neucom.2016.12.089 -
A learning system for automatic Berg Balance Scale score estimation
Engineering Applications of Artificial Intelligence. 2017-11-01. 66 : 60-74.
10.1016/j.engappai.2017.08.018 -
A reservoir computing approach for balance assessment
Lecture Notes in Computer Science. 2016-01-01. : 65-77.
10.1007/978-3-319-44412-3_5