Gilles Blanchard
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Statistics and Probability top 2%
- Computational Mechanics top 10%
- Signal Processing top 5%
- Co-authors
- Clayton ScottGyemin LeeBenjamin BlankertzOlivier BousquetPascal MassartLaurent ZwaldÉtienne RoquainNicolas Vayatis
- Topics
- Statistical Methods and Inference (18 papers)Sparse and Compressive Sensing Techniques (11 papers)Machine Learning and Algorithms (10 papers)
- Journals
- Scientific ReportsIEEE Transactions on Information TheoryIEEE Transactions on Biomedical Engineering
- Partner nations
- GermanyFranceUnited States
In The Last Decade
Gilles Blanchard
49 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 561
- Computer Vision and Pattern Recognition 257
- Statistics and Probability 225
- Computational Mechanics 133
- Signal Processing 117
Countries citing papers authored by Gilles Blanchard
This map shows the geographic impact of Gilles Blanchard'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 Gilles Blanchard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gilles Blanchard more than expected).
Fields of papers citing papers by Gilles Blanchard
This network shows the impact of papers produced by Gilles Blanchard. 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 Gilles Blanchard. The network helps show where Gilles Blanchard may publish in the future.
Co-authorship network of co-authors of Gilles Blanchard
This figure shows the co-authorship network connecting the top 25 collaborators of Gilles Blanchard. A scholar is included among the top collaborators of Gilles Blanchard 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 Gilles Blanchard. Gilles Blanchard 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 | 0 | |
| 3 | Decontamination of Mutual Contamination Models | 1 |
| 4 | Parallelizing Spectrally Regularized Kernel Algorithms | 18 |
| 5 | 2 | |
| 6 | 8 | |
| 7 | 3 | |
| 8 | 20 | |
| 9 | 47 | |
| 10 | 12 | |
| 11 | 53 | |
| 12 | Classification with asymmetric label noise: Consistency and maximal denoising | 25 |
| 13 | Generalizing from Several Related Classification Tasks to a New Unlabeled Sample | 139 |
| 14 | Kernel Partial Least Squares is Universally Consistent | 6 |
| 15 | 115 | |
| 16 | Novelty detection: Unlabeled data definitely help | 30 |
| 17 | 23 | |
| 18 | Self-consistent multiple testing procedures | 0 |
| 19 | Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction | 4 |
| 20 | 66 |
About Gilles Blanchard
Gilles Blanchard is a scholar working on Statistics and Probability, Mathematical Physics and Artificial Intelligence, having authored 53 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistical Methods and Inference (18 papers), Sparse and Compressive Sensing Techniques (11 papers) and Machine Learning and Algorithms (10 papers). The work is most often cited by research in Statistics and Probability (225 citations), Artificial Intelligence (561 citations) and Computer Vision and Pattern Recognition (257 citations). Gilles Blanchard has collaborated with scholars based in Germany, France and United States. Frequent co-authors include Clayton Scott, Gyemin Lee, Benjamin Blankertz, Olivier Bousquet, Pascal Massart, Laurent Zwald, Étienne Roquain, Nicolas Vayatis, Gábor Lugosi and Donald Geman. Their work appears in journals such as Scientific Reports, IEEE Transactions on Information Theory and IEEE Transactions on Biomedical Engineering.
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.