Davide Bacciu
Impact in
- Artificial Intelligence top 1%
- Domain Adaptation and Few-Shot Learning
- Advanced Graph Neural Networks
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Explainable Artificial Intelligence (XAI)
- Computational Mathematics top 5%
Papers in
-
- Advanced Graph Neural Networks 25
- Neural Networks and Applications 22
- Domain Adaptation and Few-Shot Learning 18
- Neural Networks and Reservoir Computing 15
- Natural Language Processing Techniques 10
- Bayesian Modeling and Causal Inference 9
- Topic Modeling 8
- Co-authors
- Alessio Micheli (45 shared papers)Marco Podda (9 shared papers)Antonio Carta (23 shared papers)Federico Errica (9 shared papers)Andrea Cossu (19 shared papers)Claudio Gallicchio (37 shared papers)Vincenzo Lomonaco (19 shared papers)Stefano Chessa (14 shared papers)
- Journals
- Neurocomputing (14 papers)IEEE Transactions on Neural Networks and Learning Systems (6 papers)Neural Networks (3 papers)Neural Computing and Applications (3 papers)Lecture notes in computer science (20 papers)
- Partner nations
- ItalyUnited KingdomGermany
In The Last Decade
Davide Bacciu
162 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 115
- Artificial Intelligence 858
- Computational Mathematics 15
- Computer Vision and Pattern Recognition 176
- Information Systems 161
- Signal Processing 53
Countries citing papers authored by Davide Bacciu
This map shows the geographic impact of Davide Bacciu'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 Davide Bacciu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davide Bacciu more than expected).
Fields of papers citing papers by Davide Bacciu
This network shows the impact of papers produced by Davide Bacciu. 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 Davide Bacciu. The network helps show where Davide Bacciu may publish in the future.
Co-authors
The 25 scholars most cited alongside Davide Bacciu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 187 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 222 | |
| 2 | 2021 | 99 | |
| 3 | 2013 | 89 | |
| 4 | 2021 | 88 | |
| 5 | 2019 | 67 | |
| 6 | 2018 | 66 | |
| 7 | 2012 | 36 | |
| 8 | 2022 | 35 | |
| 9 | 2017 | 32 | |
| 10 | 2015 | 31 | |
| 11 | 2015 | 29 | |
| 12 | Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms | 2017 | 28 |
| 13 | 2022 | 26 | |
| 14 | 2019 | 24 | |
| 15 | 2021 | 24 | |
| 16 | 2022 | 24 | |
| 17 | 2016 | 23 | |
| 18 | 2022 | 23 | |
| 19 | 2021 | 22 | |
| 20 | 2022 | 21 |
About Davide Bacciu
Davide Bacciu is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 187 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (25 papers), Neural Networks and Applications (22 papers), Domain Adaptation and Few-Shot Learning (18 papers), Neural Networks and Reservoir Computing (15 papers), Natural Language Processing Techniques (10 papers), Context-Aware Activity Recognition Systems (9 papers), Bayesian Modeling and Causal Inference (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Artificial Intelligence (858 citations), Computational Mathematics (15 citations), Computer Vision and Pattern Recognition (176 citations), Information Systems (161 citations) and Signal Processing (53 citations). Davide Bacciu has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include Alessio Micheli, Marco Podda, Antonio Carta, Federico Errica, Andrea Cossu, Claudio Gallicchio, Vincenzo Lomonaco, Stefano Chessa, Alessandro Sperduti and Paolo Barsocchi. Their work appears in journals such as Neurocomputing, IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Neural Computing and Applications and Lecture notes in computer science.
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.