Mikael Henaff
Impact in
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- Advanced Neural Network Applications
- Computational Mathematics top 10%
Papers in
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- Reinforcement Learning in Robotics 4
- Neural Networks and Applications 2
- Explainable Artificial Intelligence (XAI) 2
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- Gene expression and cancer classification 3
- Machine Learning in Bioinformatics 2
- Metabolomics and Mass Spectrometry Studies 2
- Co-authors
- Yann LeCun (9 shared papers)Michaël Mathieu (4 shared papers)Gérard Ben Arous (2 shared papers)Anna Choromanska (2 shared papers)Constantin Aliferis (5 shared papers)Alexander Statnikov (5 shared papers)Martin J. Blaser (2 shared papers)Alexander V. Alekseyenko (2 shared papers)
- Journals
- Scientific Reports (2 papers)BMC Genomics (1 paper)Microbiome (1 paper)Journal of Machine Learning Research (1 paper)International Conference on Learning Representations (4 papers)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Mikael Henaff
18 papers receiving 958 citations
Peers
Comparison fields: 5 of 134
- Computer Vision and Pattern Recognition 359
- Computational Mathematics 9
- Artificial Intelligence 456
- Signal Processing 100
- Dermatology 36
Countries citing papers authored by Mikael Henaff
This map shows the geographic impact of Mikael Henaff'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 Mikael Henaff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikael Henaff more than expected).
Fields of papers citing papers by Mikael Henaff
This network shows the impact of papers produced by Mikael Henaff. 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 Mikael Henaff. The network helps show where Mikael Henaff may publish in the future.
Co-authors
The 25 scholars most cited alongside Mikael Henaff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 284 | |
| 2 | Fast Training of Convolutional Networks through FFTs | 2014 | 228 |
| 3 | 2013 | 152 | |
| 4 | 2016 | 70 | |
| 5 | 2011 | 68 | |
| 6 | 2013 | 60 | |
| 7 | The Loss Surface of Multilayer Networks. | 2014 | 30 |
| 8 | 2014 | 24 | |
| 9 | 2012 | 19 | |
| 10 | Disagreement-Regularized Imitation Learning | 2020 | 16 |
| 11 | 2015 | 11 | |
| 12 | Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic | 2019 | 6 |
| 13 | Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning | 2020 | 6 |
| 14 | Recurrent orthogonal networks and long-memory tasks | 2016 | 6 |
| 15 | Fast training of convolutional networks through FFTS: International Conference on Learning Representations (ICLR2014), CBLS, April 2014 | 2014 | 5 |
| 16 | 2019 | 5 | |
| 17 | Model-Based Planning in Discrete Action Spaces. | 2017 | 3 |
| 18 | 2025 | 2 |
About Mikael Henaff
Mikael Henaff is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Signal Processing, having authored 18 papers that have together received 995 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Gene expression and cancer classification (3 papers), Machine Learning in Bioinformatics (2 papers), Neural Networks and Applications (2 papers), Advanced Bandit Algorithms Research (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Music and Audio Processing (2 papers) and Explainable Artificial Intelligence (XAI) (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (359 citations), Computational Mathematics (9 citations), Artificial Intelligence (456 citations), Signal Processing (100 citations) and Dermatology (36 citations). Mikael Henaff has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Yann LeCun, Michaël Mathieu, Gérard Ben Arous, Anna Choromanska, Constantin Aliferis, Alexander Statnikov, Martin J. Blaser, Alexander V. Alekseyenko, Koray Kavukcuoglu and Arthur Szlam. Their work appears in journals such as Scientific Reports, BMC Genomics, Microbiome, Journal of Machine Learning Research and International Conference on Learning Representations.
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.