Edgar Dobriban

1.2k total citations
35 papers, 390 citations indexed

About

Edgar Dobriban is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Edgar Dobriban has authored 35 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 15 papers in Artificial Intelligence and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Edgar Dobriban's work include Random Matrices and Applications (8 papers), Statistical Methods and Inference (7 papers) and Sparse and Compressive Sensing Techniques (5 papers). Edgar Dobriban is often cited by papers focused on Random Matrices and Applications (8 papers), Statistical Methods and Inference (7 papers) and Sparse and Compressive Sensing Techniques (5 papers). Edgar Dobriban collaborates with scholars based in United States, China and Italy. Edgar Dobriban's co-authors include Zhichao Hou, Kun Qian, Art B. Owen, Stuart K. Kim, Kristen Fortney, Sifan Liu, Chiara Pirazzini, Daniela Monti, Gil Atzmon and Paolo Garagnani and has published in prestigious journals such as Nature Communications, Journal of the American Statistical Association and Biometrics.

In The Last Decade

Edgar Dobriban

33 papers receiving 376 citations

Peers

Edgar Dobriban
Comparison fields: 5 of 97
  • Statistics and Probability 86
  • Civil and Structural Engineering 85
  • Artificial Intelligence 85
  • Molecular Biology 59
  • Aging 46
Replace Yoshihiro Mitani with:
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Yoshihiro Mitani Japan View profile →
Citations per field, relative to Edgar Dobriban
Edgar Dobriban · 1×
Citations per year, relative to Edgar Dobriban
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Countries citing papers authored by Edgar Dobriban

Since Specialization
Citations

This map shows the geographic impact of Edgar Dobriban'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 Edgar Dobriban with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edgar Dobriban more than expected).

Fields of papers citing papers by Edgar Dobriban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edgar Dobriban. 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 Edgar Dobriban. The network helps show where Edgar Dobriban may publish in the future.

Co-authorship network of co-authors of Edgar Dobriban

This figure shows the co-authorship network connecting the top 25 collaborators of Edgar Dobriban. A scholar is included among the top collaborators of Edgar Dobriban 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 Edgar Dobriban. Edgar Dobriban is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 1
3 3
4 0
5 1
6 4
7 2
8 4
9 19
10
What Causes the Test Error? Going Beyond Bias-Variance via ANOVA
1
11
The Implicit Regularization of Stochastic Gradient Flow for Least Squares
3
12
Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform
5
13
One-shot distributed ridge regression in high dimensions
4
14
A New Theory for Sketching in Linear Regression.
1
15
Flexible Multiple Testing with the FACT Algorithm
2
16 4
17
Factor selection by permutation
1
18 10
19 99
20 12

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.

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