Mathieu Blondel
Impact in
- Computational Mathematics top 10%
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
Papers in
-
- Machine Learning and Algorithms 5
- Natural Language Processing Techniques 2
- Topic Modeling 2
-
- Face and Expression Recognition 5
- Co-authors
- Naonori Ueda (9 shared papers)Kuniaki Uehara (3 shared papers)Kazuhiro Seki (3 shared papers)Hiroyoshi Iwata (1 shared paper)Akio Onogi (1 shared paper)Akinori Fujino (3 shared papers)Jean‐Philippe Vert (3 shared papers)Olivier Teboul (3 shared papers)
- Journals
- The American Surgeon (1 paper)Nature Methods (1 paper)Computer Assisted Language Learning (1 paper)Journal of Medical Internet Research (1 paper)Machine Learning (1 paper)
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Mathieu Blondel
22 papers receiving 275 citations
Peers
Comparison fields: 5 of 90
- Computational Mathematics 9
- Artificial Intelligence 98
- Computer Vision and Pattern Recognition 62
- Genetics 44
- Health Information Management 7
Countries citing papers authored by Mathieu Blondel
This map shows the geographic impact of Mathieu Blondel'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 Mathieu Blondel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathieu Blondel more than expected).
Fields of papers citing papers by Mathieu Blondel
This network shows the impact of papers produced by Mathieu Blondel. 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 Mathieu Blondel. The network helps show where Mathieu Blondel may publish in the future.
Co-authors
The 25 scholars most cited alongside Mathieu Blondel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 45 | |
| 2 | 2013 | 44 | |
| 3 | 2022 | 26 | |
| 4 | 2015 | 24 | |
| 5 | Learning with Differentiable Pertubed Optimizers | 2020 | 20 |
| 6 | 2016 | 16 | |
| 7 | Smooth and Sparse Optimal Transport | 2018 | 15 |
| 8 | Polynomial networks and factorization machines: new insights and efficient training algorithms | 2016 | 14 |
| 9 | A Regularized Framework for Sparse and Structured Neural Attention | 2017 | 13 |
| 10 | {Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion} | 2014 | 13 |
| 11 | SparseMAP: Differentiable Sparse Structured Inference | 2018 | 11 |
| 12 | 2018 | 10 | |
| 13 | 2014 | 8 | |
| 14 | 2016 | 5 | |
| 15 | 2017 | 4 | |
| 16 | 2011 | 4 | |
| 17 | Differentiable Divergences Between Time Series | 2021 | 3 |
| 18 | Differentiable Dynamic Programming for Structured Prediction and Attention | 2018 | 3 |
| 19 | 2015 | 3 | |
| 20 | 2017 | 1 |
About Mathieu Blondel
Mathieu Blondel is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Molecular Biology and Signal Processing, having authored 23 papers that have together received 284 indexed citations. Recurring topics across this work include Face and Expression Recognition (5 papers), Machine Learning and Algorithms (5 papers), Sparse and Compressive Sensing Techniques (5 papers), Machine Learning in Bioinformatics (3 papers), Natural Language Processing Techniques (2 papers), Speech and Audio Processing (2 papers), Topic Modeling (2 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper). The work is most often cited by research in Computational Mathematics (9 citations), Artificial Intelligence (98 citations), Computer Vision and Pattern Recognition (62 citations), Genetics (44 citations) and Health Information Management (7 citations). Mathieu Blondel has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Naonori Ueda, Kuniaki Uehara, Kazuhiro Seki, Hiroyoshi Iwata, Akio Onogi, Akinori Fujino, Jean‐Philippe Vert, Olivier Teboul, Quentin Berthet and Vlad Niculae. Their work appears in journals such as The American Surgeon, Nature Methods, Computer Assisted Language Learning, Journal of Medical Internet Research and Machine Learning.
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.