Ramsés H. Mena
- Artificial Intelligence top 2%
- Statistics and Probability top 1%
- Finance top 10%
- Molecular Biology
- Mathematical Physics top 10%
- Co-authors
- Igor PrünsterAntonio LijoiStephen G. WalkerPierpaolo De BlasiStefano FavaroEduardo Gutiérrez‐PeñaJay ZarnikauPaul Damien
- Topics
- Bayesian Methods and Mixture Models (31 papers)Statistical Methods and Inference (12 papers)Statistical Methods and Bayesian Inference (10 papers)
- Journals
- Journal of the American Statistical AssociationIEEE Transactions on Pattern Analysis and Machine IntelligenceBiometrika
- Partner nations
- MexicoUnited KingdomItaly
In The Last Decade
Ramsés H. Mena
42 papers receiving 696 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 592
- Statistics and Probability 429
- Finance 85
- Molecular Biology 72
- Mathematical Physics 70
Countries citing papers authored by Ramsés H. Mena
This map shows the geographic impact of Ramsés H. Mena'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 Ramsés H. Mena with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramsés H. Mena more than expected).
Fields of papers citing papers by Ramsés H. Mena
This network shows the impact of papers produced by Ramsés H. Mena. 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 Ramsés H. Mena. The network helps show where Ramsés H. Mena may publish in the future.
Co-authorship network of co-authors of Ramsés H. Mena
This figure shows the co-authorship network connecting the top 25 collaborators of Ramsés H. Mena. A scholar is included among the top collaborators of Ramsés H. Mena 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 Ramsés H. Mena. Ramsés H. Mena 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 | 2 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | On GEM diffusive mixtures | 0 |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 20 | |
| 11 | 0 | |
| 12 | 93 | |
| 13 | 9 | |
| 14 | 4 | |
| 15 | 12 | |
| 16 | 25 | |
| 17 | Stationary Autoregressive Models Via a Bayesian Nonparametric Approach | 0 |
| 18 | 18 | |
| 19 | 114 | |
| 20 | 29 |
About Ramsés H. Mena
Ramsés H. Mena is a scholar working on Statistics and Probability, Finance and Artificial Intelligence, having authored 46 papers that have together received 723 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (31 papers), Statistical Methods and Inference (12 papers) and Statistical Methods and Bayesian Inference (10 papers). The work is most often cited by research in Statistics and Probability (429 citations), Artificial Intelligence (592 citations) and Finance (85 citations). Ramsés H. Mena has collaborated with scholars based in Mexico, United Kingdom and Italy. Frequent co-authors include Igor Prünster, Antonio Lijoi, Stephen G. Walker, Pierpaolo De Blasi, Stefano Favaro, Stephen G. Walker, Eduardo Gutiérrez‐Peña, Jay Zarnikau, Paul Damien and Luis E. Nieto‐Barajas. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and Biometrika.
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.