Ery Arias-Castro
- Artificial Intelligence top 2%
- Statistics and Probability top 1%
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 5%
- Renewable Energy, Sustainability and the Environment top 10%
- Co-authors
- David L. DonohoEmmanuel J. CandèsMatthew LaveJan KleisslXiaoming HuoNicolas VerzélenYaniv PlanArnaud Durand
- Topics
- Bayesian Methods and Mixture Models (13 papers)Statistical Methods and Inference (13 papers)Topological and Geometric Data Analysis (9 papers)
- Journals
- Journal of the American Statistical AssociationPLoS ONEIEEE Transactions on Information Theory
- Partner nations
- United StatesFranceNetherlands
In The Last Decade
Ery Arias-Castro
55 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 141
- Artificial Intelligence 541
- Statistics and Probability 317
- Computer Vision and Pattern Recognition 241
- Computational Mechanics 165
- Renewable Energy, Sustainability and the Environment 160
Countries citing papers authored by Ery Arias-Castro
This map shows the geographic impact of Ery Arias-Castro'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 Ery Arias-Castro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ery Arias-Castro more than expected).
Fields of papers citing papers by Ery Arias-Castro
This network shows the impact of papers produced by Ery Arias-Castro. 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 Ery Arias-Castro. The network helps show where Ery Arias-Castro may publish in the future.
Co-authorship network of co-authors of Ery Arias-Castro
This figure shows the co-authorship network connecting the top 25 collaborators of Ery Arias-Castro. A scholar is included among the top collaborators of Ery Arias-Castro 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 Ery Arias-Castro. Ery Arias-Castro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | Spectral clustering based on local PCA | 36 |
| 5 | 27 | |
| 6 | 2 | |
| 7 | 10 | |
| 8 | 54 | |
| 9 | 11 | |
| 10 | 2 | |
| 11 | 14 | |
| 12 | 12 | |
| 13 | 164 | |
| 14 | 89 | |
| 15 | 5 | |
| 16 | Simple Linear Regression | 11 |
| 17 | 44 | |
| 18 | 5 | |
| 19 | 33 | |
| 20 | 1 |
About Ery Arias-Castro
Ery Arias-Castro is a scholar working on Statistics and Probability, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 60 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (13 papers), Statistical Methods and Inference (13 papers) and Topological and Geometric Data Analysis (9 papers). The work is most often cited by research in Statistics and Probability (317 citations), Computational Mathematics (10 citations) and Artificial Intelligence (541 citations). Ery Arias-Castro has collaborated with scholars based in United States, France and Netherlands. Frequent co-authors include David L. Donoho, Emmanuel J. Candès, Matthew Lave, Jan Kleissl, Xiaoming Huo, Nicolas Verzélen, Yaniv Plan, Arnaud Durand, Gilad Lerman and Mark A. Davenport. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE and IEEE Transactions on Information Theory.
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.