Simone Bassis

501 citations
34 papers · 268 · h-index 9

Impact in

Papers in

Simone Bassis

32 papers receiving 260 citations

Peers

Simone Bassis
Comparison fields: 5 of 91
  • Statistics and Probability 45
  • Management Science and Operations Research 43
  • Artificial Intelligence 94
  • Computational Theory and Mathematics 36
  • Statistics, Probability and Uncertainty 15
Replace Anastasios N. Angelopoulos with:
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Stefano Ermon United States
Patryk Orzechowski United States
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A. H. El-Baz Egypt
Srikanth K. Iyer India
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Citations per field
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Citations per year

Countries citing papers authored by Simone Bassis

Since Specialization
Citations

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

Fields of papers citing papers by Simone Bassis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Simone Bassis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Simone Bassis Line = papers co-authored together Simone Bassis links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201663
2 201644
3 201636
4 200815
5 200913
6 200911
7 20079
8 20129
9 20088
10 20057
11 20166
12 20076
13 20154
14 20074
15
New Directions in Neural Networks: 18th Italian Workshop on Neural Networks WIRN 2008 - Volume 193 Frontiers in Artificial Intelligence and Applications
20093
16 20053
17 20073
18 20113
19 20113
20
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
20113

About Simone Bassis

Simone Bassis is a scholar working on Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 34 papers that have together received 268 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Machine Learning and Algorithms (5 papers), Rough Sets and Fuzzy Logic (4 papers), Advanced Memory and Neural Computing (3 papers), Statistical Methods and Inference (3 papers), Neural dynamics and brain function (3 papers), Machine Learning and Data Classification (3 papers) and Experimental Behavioral Economics Studies (2 papers). The work is most often cited by research in Statistics and Probability (45 citations), Management Science and Operations Research (43 citations), Artificial Intelligence (94 citations), Computational Theory and Mathematics (36 citations) and Statistics, Probability and Uncertainty (15 citations). Simone Bassis has collaborated with scholars based in Italy, Switzerland and Canada. Frequent co-authors include Bruno Apolloni, Anna Esposito, Francesco Carlo Morabito, Eros Pasero, Dario Malchiodi, Sabrina Gaito, Witold Pedrycz, Chiara Locatelli, S. Crosara and Cecilia Quintavalla. Their work appears in journals such as Information Sciences, Nonlinear Analysis Hybrid Systems, Nonlinear Analysis, Neurocomputing and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).

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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