Daniele Tantari
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Condensed Matter Physics top 10%
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Adriano BarraGiuseppe GenovesePeter SollichFabrizio LilloElena AgliariAlessia AnnibaleFrancesco GuerraPaolo Barucca
- Topics
- Theoretical and Computational Physics (13 papers)Complex Systems and Time Series Analysis (9 papers)Neural Networks and Applications (9 papers)
- Partner nations
- ItalyUnited KingdomSwitzerland
In The Last Decade
Daniele Tantari
30 papers receiving 408 citations
Peers
Comparison fields: 5 of 74
- Statistical and Nonlinear Physics 168
- Artificial Intelligence 164
- Condensed Matter Physics 105
- Cognitive Neuroscience 96
- Computer Vision and Pattern Recognition 94
Countries citing papers authored by Daniele Tantari
This map shows the geographic impact of Daniele Tantari'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 Daniele Tantari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniele Tantari more than expected).
Fields of papers citing papers by Daniele Tantari
This network shows the impact of papers produced by Daniele Tantari. 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 Daniele Tantari. The network helps show where Daniele Tantari may publish in the future.
Co-authorship network of co-authors of Daniele Tantari
This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Tantari. A scholar is included among the top collaborators of Daniele Tantari 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 Daniele Tantari. Daniele Tantari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 9 | |
| 7 | 9 | |
| 8 | 9 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | 33 | |
| 12 | 53 | |
| 13 | 38 | |
| 14 | 2 | |
| 15 | 9 | |
| 16 | 5 | |
| 17 | 33 | |
| 18 | 43 | |
| 19 | 18 | |
| 20 | How much glassy are neural networks | 1 |
About Daniele Tantari
Daniele Tantari is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics and Statistics and Probability, having authored 31 papers that have together received 431 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (13 papers), Complex Systems and Time Series Analysis (9 papers) and Neural Networks and Applications (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (168 citations), Condensed Matter Physics (105 citations) and Statistics and Probability (45 citations). Daniele Tantari has collaborated with scholars based in Italy, United Kingdom and Switzerland. Frequent co-authors include Adriano Barra, Giuseppe Genovese, Peter Sollich, Fabrizio Lillo, Elena Agliari, Alessia Annibale, Francesco Guerra, Paolo Barucca, Andrea Galluzzi and Pierluigi Contucci. Their work appears in journals such as Physical Review Letters, PLoS ONE and Scientific Reports.
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.