Rafael Izbicki
- Geriatrics and Gerontology top 2%
- Physiology
- Psychiatry and Mental health top 10%
- Artificial Intelligence top 10%
- Economics and Econometrics top 10%
- Co-authors
- Iván AprahamianMônica Sanches YassudaAnn B. LeeDavid C. SteffensRicardo Barcelos‐FerreiraCássio M. C. BottinoLúcio Garcia de OliveiraArthur Guerra de Andrade
- Topics
- Statistical Methods and Inference (13 papers)Machine Learning and Data Classification (7 papers)Bayesian Methods and Mixture Models (6 papers)
- Cited by
- Geriatrics and GerontologyStatistics and ProbabilityNeuropsychology and Physiological Psychology
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONERemote Sensing of Environment
- Partner nations
- BrazilUnited StatesMoldova
In The Last Decade
Rafael Izbicki
52 papers receiving 787 citations
Peers
Comparison fields: 5 of 152
- Geriatrics and Gerontology 182
- Physiology 140
- Psychiatry and Mental health 122
- Artificial Intelligence 103
- Economics and Econometrics 99
Countries citing papers authored by Rafael Izbicki
This map shows the geographic impact of Rafael Izbicki'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 Rafael Izbicki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafael Izbicki more than expected).
Fields of papers citing papers by Rafael Izbicki
This network shows the impact of papers produced by Rafael Izbicki. 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 Rafael Izbicki. The network helps show where Rafael Izbicki may publish in the future.
Co-authorship network of co-authors of Rafael Izbicki
This figure shows the co-authorship network connecting the top 25 collaborators of Rafael Izbicki. A scholar is included among the top collaborators of Rafael Izbicki 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 Rafael Izbicki. Rafael Izbicki 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 | 3 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 23 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 21 | |
| 13 | Flexible distribution-free conditional predictive bands using density estimators. | 2 |
| 14 | Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations | 2 |
| 15 | NNKCDE: Nearest Neighbor Kernel Conditional Density Estimation | 1 |
| 16 | 12 | |
| 17 | 4 | |
| 18 | 2 | |
| 19 | 4 | |
| 20 | 76 |
About Rafael Izbicki
Rafael Izbicki is a scholar working on Statistics and Probability, Geriatrics and Gerontology and Artificial Intelligence, having authored 59 papers that have together received 810 indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Machine Learning and Data Classification (7 papers) and Bayesian Methods and Mixture Models (6 papers). The work is most often cited by research in Geriatrics and Gerontology (182 citations), Statistics and Probability (87 citations) and Neuropsychology and Physiological Psychology (14 citations). Rafael Izbicki has collaborated with scholars based in Brazil, United States and Moldova. Frequent co-authors include Iván Aprahamian, Mônica Sanches Yassuda, Ann B. Lee, David C. Steffens, Ricardo Barcelos‐Ferreira, Cássio M. C. Bottino, Lúcio Garcia de Oliveira, Arthur Guerra de Andrade, Alexander Moreira‐Almeida and Marina Maria Biella. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Remote Sensing of Environment.
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.