Stefano Favaro
- Artificial Intelligence top 5%
- Statistics and Probability top 2%
- Mathematical Physics top 10%
- Molecular Biology
- Finance top 10%
- Co-authors
- Igor PrünsterYee Whye TehAntonio LijoiRamsés H. MenaStephen G. WalkerPierpaolo De BlasiLorenzo TrippaSergio Bacallado
- Topics
- Bayesian Methods and Mixture Models (45 papers)Statistical Methods and Inference (17 papers)Statistical Methods and Bayesian Inference (15 papers)
- Journals
- Journal of the American Statistical AssociationPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Stefano Favaro
53 papers receiving 438 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 368
- Statistics and Probability 256
- Mathematical Physics 77
- Molecular Biology 51
- Finance 37
Countries citing papers authored by Stefano Favaro
This map shows the geographic impact of Stefano Favaro'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 Stefano Favaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Favaro more than expected).
Fields of papers citing papers by Stefano Favaro
This network shows the impact of papers produced by Stefano Favaro. 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 Stefano Favaro. The network helps show where Stefano Favaro may publish in the future.
Co-authorship network of co-authors of Stefano Favaro
This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Favaro. A scholar is included among the top collaborators of Stefano Favaro 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 Stefano Favaro. Stefano Favaro 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 | 0 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | Consistent estimation of small masses in feature sampling | 1 |
| 7 | 1 | |
| 8 | 5 | |
| 9 | Stable behaviour of infinitely wide deep neural networks. | 1 |
| 10 | 3 | |
| 11 | 0 | |
| 12 | Neural Stochastic Differential Equations. | 1 |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 8 | |
| 16 | 28 | |
| 17 | 24 | |
| 18 | 5 | |
| 19 | 17 | |
| 20 | 9 |
About Stefano Favaro
Stefano Favaro is a scholar working on Statistics and Probability, Artificial Intelligence and Mathematical Physics, having authored 60 papers that have together received 452 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (45 papers), Statistical Methods and Inference (17 papers) and Statistical Methods and Bayesian Inference (15 papers). The work is most often cited by research in Statistics and Probability (256 citations), Artificial Intelligence (368 citations) and Mathematical Physics (77 citations). Stefano Favaro has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Igor Prünster, Yee Whye Teh, Antonio Lijoi, Ramsés H. Mena, Stephen G. Walker, Pierpaolo De Blasi, Lorenzo Trippa, Sergio Bacallado, Shui Feng and Stephen G. Walker. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.