Stefania Fresca
- Statistical and Nonlinear Physics top 2%
- Computational Mechanics top 5%
- Statistics, Probability and Uncertainty top 2%
- Aerospace Engineering
- Control and Systems Engineering
- Co-authors
- Andrea ManzoniGiorgio GobatAlfio QuarteroniAttilio FrangiLuca Dede’Paolo ZuninoPatrick FedeliAndrea Opreni
- Topics
- Model Reduction and Neural Networks (20 papers)Probabilistic and Robust Engineering Design (7 papers)Numerical methods for differential equations (5 papers)
- Cited by
- Statistical and Nonlinear PhysicsStatistics, Probability and UncertaintyComputational Mechanics
- Partner nations
- ItalySwitzerlandNetherlands
In The Last Decade
Stefania Fresca
20 papers receiving 482 citations
Hit Papers
Peers
Comparison fields: 5 of 54
- Statistical and Nonlinear Physics 370
- Computational Mechanics 173
- Statistics, Probability and Uncertainty 142
- Aerospace Engineering 65
- Control and Systems Engineering 60
Countries citing papers authored by Stefania Fresca
This map shows the geographic impact of Stefania Fresca'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 Stefania Fresca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefania Fresca more than expected).
Fields of papers citing papers by Stefania Fresca
This network shows the impact of papers produced by Stefania Fresca. 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 Stefania Fresca. The network helps show where Stefania Fresca may publish in the future.
Co-authorship network of co-authors of Stefania Fresca
This figure shows the co-authorship network connecting the top 25 collaborators of Stefania Fresca. A scholar is included among the top collaborators of Stefania Fresca 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 Stefania Fresca. Stefania Fresca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 8 | |
| 4 | 9 | |
| 5 | 17 | |
| 6 | 15 | |
| 7 | 6 | |
| 8 | 11 | |
| 9 | 13 | |
| 10 | 8 | |
| 11 | 39 | |
| 12 | POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decompositionbreakdown → | 164 |
| 13 | 30 | |
| 14 | 26 | |
| 15 | 23 | |
| 16 | 11 | |
| 17 | 37 | |
| 18 | 23 | |
| 19 | Deep learning-based reduced order models for nonlinear parametrized PDEs: application to cardiac electrophysiology | 1 |
| 20 | 49 |
About Stefania Fresca
Stefania Fresca is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 21 papers that have together received 502 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (20 papers), Probabilistic and Robust Engineering Design (7 papers) and Numerical methods for differential equations (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (370 citations), Statistics, Probability and Uncertainty (142 citations) and Computational Mechanics (173 citations). Stefania Fresca has collaborated with scholars based in Italy, Switzerland and Netherlands. Frequent co-authors include Andrea Manzoni, Giorgio Gobat, Alfio Quarteroni, Attilio Frangi, Luca Dede’, Paolo Zunino, Patrick Fedeli, Andrea Opreni, Mengwu Guo and Stefano Pagani. Their work appears in journals such as PLoS ONE, Computer Methods in Applied Mechanics and Engineering and Sensors.
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.