Marten Wegkamp
- Statistics and Probability top 0.5%
- Artificial Intelligence top 2%
- Finance top 2%
- Computational Mechanics top 10%
- Management Science and Operations Research top 5%
- Co-authors
- Jean‐David FermanianPeter L. BartlettDragan RadulovićFlorentina BuneaAlexandre B. TsybakovRadu HerbeiGérard BiauMing Yuan
- Topics
- Statistical Methods and Inference (26 papers)Bayesian Methods and Mixture Models (9 papers)Advanced Statistical Methods and Models (9 papers)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Marten Wegkamp
40 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 114
- Statistics and Probability 613
- Artificial Intelligence 517
- Finance 277
- Computational Mechanics 137
- Management Science and Operations Research 124
Countries citing papers authored by Marten Wegkamp
This map shows the geographic impact of Marten Wegkamp'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 Marten Wegkamp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marten Wegkamp more than expected).
Fields of papers citing papers by Marten Wegkamp
This network shows the impact of papers produced by Marten Wegkamp. 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 Marten Wegkamp. The network helps show where Marten Wegkamp may publish in the future.
Co-authorship network of co-authors of Marten Wegkamp
This figure shows the co-authorship network connecting the top 25 collaborators of Marten Wegkamp. A scholar is included among the top collaborators of Marten Wegkamp 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 Marten Wegkamp. Marten Wegkamp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond | 2 |
| 5 | 14 | |
| 6 | Essential regression | 2 |
| 7 | 29 | |
| 8 | Analysis of elliptical copula correlation factor model with Kendall's tau | 3 |
| 9 | 35 | |
| 10 | Classification Methods with Reject Option Based on Convex Risk Minimization | 56 |
| 11 | Adaptive Rank Penalized Estimators in Multivariate Regression | 6 |
| 12 | 192 | |
| 13 | 6 | |
| 14 | Sparsity oracle inequalities for the Lasso | 196 |
| 15 | 16 | |
| 16 | 35 | |
| 17 | 17 | |
| 18 | 2 | |
| 19 | Entropy methods in statistical estimation | 5 |
| 20 | 2 |
About Marten Wegkamp
Marten Wegkamp is a scholar working on Statistics and Probability, Artificial Intelligence and Finance, having authored 42 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods and Inference (26 papers), Bayesian Methods and Mixture Models (9 papers) and Advanced Statistical Methods and Models (9 papers). The work is most often cited by research in Statistics and Probability (613 citations), Finance (277 citations) and Artificial Intelligence (517 citations). Marten Wegkamp has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Jean‐David Fermanian, Peter L. Bartlett, Dragan Radulović, Florentina Bunea, Alexandre B. Tsybakov, Radu Herbei, Gérard Biau, Ming Yuan, Donald J. Brown and Sara van de Geer. Their work appears in journals such as Econometrica, Nature Methods 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.