Bálint Pataki
- Astronomy and Astrophysics top 10%
- Artificial Intelligence
- Epidemiology
- Public Health, Environmental and Occupational Health
- Obstetrics and Gynecology
- Co-authors
- István CsabaiDezső RibliJosé Manuel Zorrilla MatillaDaniel HsuZoltán HaimanRoger EritjaJohn R.B. PalmerFrederic Bartumeus
- Topics
- Galaxies: Formation, Evolution, Phenomena (3 papers)Gaussian Processes and Bayesian Inference (3 papers)Radiomics and Machine Learning in Medical Imaging (1 paper)
- Journals
- Scientific ReportsMonthly Notices of the Royal Astronomical SocietyThe European Physical Journal B
- Partner nations
- HungaryUnited KingdomUnited States
In The Last Decade
Bálint Pataki
8 papers receiving 238 citations
Peers
Comparison fields: 5 of 79
- Astronomy and Astrophysics 88
- Artificial Intelligence 47
- Epidemiology 41
- Public Health, Environmental and Occupational Health 38
- Obstetrics and Gynecology 34
Countries citing papers authored by Bálint Pataki
This map shows the geographic impact of Bálint Pataki'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 Bálint Pataki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bálint Pataki more than expected).
Fields of papers citing papers by Bálint Pataki
This network shows the impact of papers produced by Bálint Pataki. 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 Bálint Pataki. The network helps show where Bálint Pataki may publish in the future.
Co-authorship network of co-authors of Bálint Pataki
This figure shows the co-authorship network connecting the top 25 collaborators of Bálint Pataki. A scholar is included among the top collaborators of Bálint Pataki 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 Bálint Pataki. Bálint Pataki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 2 | |
| 3 | 49 | |
| 4 | 57 | |
| 5 | 8 | |
| 6 | 69 | |
| 7 | Learning from deep learning: better cosmological parameter inference from weak lensing maps | 0 |
| 8 | 39 | |
| 9 | 5 |
About Bálint Pataki
Bálint Pataki is a scholar working on Astronomy and Astrophysics, Ecological Modeling and Clinical Biochemistry, having authored 9 papers that have together received 247 indexed citations. Recurring topics across this work include Galaxies: Formation, Evolution, Phenomena (3 papers), Gaussian Processes and Bayesian Inference (3 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Astronomy and Astrophysics (88 citations), Instrumentation (16 citations) and Obstetrics and Gynecology (34 citations). Bálint Pataki has collaborated with scholars based in Hungary, United Kingdom and United States. Frequent co-authors include István Csabai, Dezső Ribli, José Manuel Zorrilla Matilla, Daniel Hsu, Zoltán Haiman, Roger Eritja, John R.B. Palmer, Frederic Bartumeus, Joan Garriga and Tinnakorn Chaiworapongsa. Their work appears in journals such as Scientific Reports, Monthly Notices of the Royal Astronomical Society and The European Physical Journal B.
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.