Luca Pedrelli
Impact in
- Artificial Intelligence top 5%
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Machine Learning and ELM
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- Advanced Memory and Neural Computing
- Optical Network Technologies
- Energy Load and Power Forecasting
Papers in
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- Neural Networks and Reservoir Computing 7
- Neural Networks and Applications 3
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- Neural dynamics and brain function 3
- Co-authors
- Claudio Gallicchio (5 shared papers)Alessio Micheli (6 shared papers)Xavier Hinaut (2 shared papers)Federico Vozzi (3 shared papers)Oberdan Parodi (2 shared papers)Stefano Chessa (1 shared paper)Filippo Palumbo (1 shared paper)Davide Bacciu (1 shared paper)
- Journals
- Pharmaceuticals (1 paper)Engineering Applications of Artificial Intelligence (1 paper)Neural Networks (1 paper)Heliyon (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- ItalySwitzerlandFrance
In The Last Decade
Luca Pedrelli
9 papers receiving 514 citations
Luca Pedrelli's Hit Papers
Peers
Comparison fields: 5 of 66
- Artificial Intelligence 450
- Electrical and Electronic Engineering 335
- Cognitive Neuroscience 93
- Physical Therapy, Sports Therapy and Rehabilitation 14
- Statistical and Nonlinear Physics 36
Countries citing papers authored by Luca Pedrelli
This map shows the geographic impact of Luca Pedrelli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luca Pedrelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Pedrelli more than expected).
Fields of papers citing papers by Luca Pedrelli
This network shows the impact of papers produced by Luca Pedrelli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luca Pedrelli. The network helps show where Luca Pedrelli may publish in the future.
Co-authors
The 24 scholars most cited alongside Luca Pedrelli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep reservoir computing: A critical experimental analysis Hit paper breakdown → | 2017 | 322 |
| 2 | 2018 | 158 | |
| 3 | 2017 | 26 | |
| 4 | 2019 | 8 | |
| 5 | 2021 | 7 | |
| 6 | 2020 | 4 | |
| 7 | 2024 | 3 | |
| 8 | 2020 | 3 | |
| 9 | Preliminary experimental analysis of reservoir computing approach for balance assessment | 2015 | 1 |
| 10 | Comparison between DeepESNs and gated RNNs on multivariate time-series prediction. | 2018 | 1 |
About Luca Pedrelli
Luca Pedrelli is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Electrical and Electronic Engineering, Molecular Biology and Structural Biology, having authored 10 papers that have together received 533 indexed citations. Recurring topics across this work include Neural Networks and Reservoir Computing (7 papers), Neural Networks and Applications (3 papers), Advanced Memory and Neural Computing (3 papers), Neural dynamics and brain function (3 papers), Cardiac electrophysiology and arrhythmias (1 paper), Analog and Mixed-Signal Circuit Design (1 paper), ECG Monitoring and Analysis (1 paper) and Monoclonal and Polyclonal Antibodies Research (1 paper). The work is most often cited by research in Artificial Intelligence (450 citations), Electrical and Electronic Engineering (335 citations), Cognitive Neuroscience (93 citations), Physical Therapy, Sports Therapy and Rehabilitation (14 citations) and Statistical and Nonlinear Physics (36 citations). Luca Pedrelli has collaborated with scholars based in Italy, Switzerland and France. Frequent co-authors include Claudio Gallicchio, Alessio Micheli, Xavier Hinaut, Federico Vozzi, Oberdan Parodi, Stefano Chessa, Filippo Palumbo, Davide Bacciu, Erina Ferro and Davide La Rosa. Their work appears in journals such as Pharmaceuticals, Engineering Applications of Artificial Intelligence, Neural Networks, Heliyon and IEEE Transactions on Neural Networks and Learning Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.