Marco Picone

567 total citations
27 papers, 276 citations indexed

About

Marco Picone is a scholar working on Oceanography, Artificial Intelligence and Atmospheric Science. According to data from OpenAlex, Marco Picone has authored 27 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Oceanography, 9 papers in Artificial Intelligence and 8 papers in Atmospheric Science. Recurrent topics in Marco Picone's work include Ocean Waves and Remote Sensing (11 papers), Oceanographic and Atmospheric Processes (9 papers) and Bayesian Methods and Mixture Models (8 papers). Marco Picone is often cited by papers focused on Ocean Waves and Remote Sensing (11 papers), Oceanographic and Atmospheric Processes (9 papers) and Bayesian Methods and Mixture Models (8 papers). Marco Picone collaborates with scholars based in Italy, Malta and United Kingdom. Marco Picone's co-authors include Francesco Lagona, Antonello Maruotti, Jan Bulla, Enrico Zambianchi, Simone Cosoli, Flavio Cannavò, Andrea Cannata, Andrea Barbanti, S. Gresta and Giuseppe Di Grazia and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and Sensors.

In The Last Decade

Marco Picone

23 papers receiving 264 citations

Peers

Marco Picone
Comparison fields: 5 of 64
  • Artificial Intelligence 103
  • Oceanography 79
  • Atmospheric Science 57
  • Environmental Engineering 50
  • Statistics and Probability 46
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Hongcheng Guo United States
Liliane Bel France
John T. Bruun United Kingdom
C. Thompson New Zealand
Wenping He China
Enrica Bellone United Kingdom
Ashutosh Chamoli India
A.V. Kashnitskii Russia
Nicholas R. Cavanaugh United States
Frank Woodcock Australia
Hongcheng Guo United States View profile →
Citations per field, relative to Marco Picone
Marco Picone · 1×
Citations per year, relative to Marco Picone
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Countries citing papers authored by Marco Picone

Since Specialization
Citations

This map shows the geographic impact of Marco Picone'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 Marco Picone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Picone more than expected).

Fields of papers citing papers by Marco Picone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Picone. 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 Marco Picone. The network helps show where Marco Picone may publish in the future.

Co-authorship network of co-authors of Marco Picone

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Picone. A scholar is included among the top collaborators of Marco Picone based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marco Picone. Marco Picone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 5
3 0
4 0
5 0
6 4
7 14
8 4
9 2
10 12
11 14
12 15
13 2
14 15
15
Environmental conditions in semi-enclosed basins: A dynamic latent class approach for mixed-type multivariate variables
5
16
Extreme Events and Sea Waves along Italian Coasts
1
17 39
18 12
19 17
20
A latent-class approach to missing value imputation in incomplete multivariate wave metric datasets
1

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.

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