| Profiling fetal cardiac function in twin–twin transfusion syndrome JJ Stirnemann, M Mougeot, F Proulx, B Nasr, M Essaoui, JC Fouron, ... Ultrasound in Obstetrics and Gynecology: The Official Journal of the …, 2010 | 155 | 2010 |
| Profiling fetal cardiac function in twin–twin transfusion syndrome JJ Stirnemann, M Mougeot, F Proulx, B Nasr, M Essaoui, JC Fouron, ... Ultrasound in Obstetrics and Gynecology: The Official Journal of the …, 2010 | 155 | 2010 |
| Image compression with back propagation: improvement of the visual restoration using different cost functions M Mougeot, R Azencott, B Angeniol Neural networks 4 (4), 467-476, 1991 | 90 | 1991 |
| Fall detection using smart floor sensor and supervised learning L Minvielle, M Atiq, R Serra, M Mougeot, N Vayatis 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 44 | 2017 |
| Statistical learning for wind power: A modeling and stability study towards forecasting A Fischer, L Montuelle, M Mougeot, D Picard Wind Energy 20 (12), 2037-2047, 2017 | 41 | 2017 |
| Adapt: Awesome domain adaptation python toolbox A de Mathelin, M Atiq, G Richard, A de la Concha, M Yachouti, ... arXiv preprint arXiv:2107.03049, 2021 | 38 | 2021 |
| Adversarial weighting for domain adaptation in regression A De Mathelin, G Richard, F Deheeger, M Mougeot, N Vayatis 2021 IEEE 33rd International Conference on Tools with Artificial …, 2021 | 33 | 2021 |
| Unsupervised multi-source domain adaptation for regression G Richard, A Mathelin, G Hébrail, M Mougeot, N Vayatis Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 22 | 2021 |
| Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: An application to rubber calendering process TNK Nguyen, T Dairay, R Meunier, M Mougeot Engineering Applications of Artificial Intelligence 114, 105176, 2022 | 20 | 2022 |
| Discrepancy-based active learning for domain adaptation A De Mathelin, F Deheeger, M Mougeot, N Vayatis arXiv preprint arXiv:2103.03757, 2021 | 20* | 2021 |
| Learning out of leaders G Kerkyacharian, M Mougeot, D Picard, K Tribouley Multiscale, Nonlinear and Adaptive Approximation: Dedicated to Wolfgang …, 2009 | 20 | 2009 |
| Predicting job power consumption based on rjms submission data in hpc systems T Saillant, JC Weill, M Mougeot High Performance Computing: 35th International Conference, ISC High …, 2020 | 18 | 2020 |
| Aggregation using input–output trade-off A Fischer, M Mougeot Journal of Statistical Planning and Inference 200, 1-19, 2019 | 17 | 2019 |
| From numerical weather prediction outputs to accurate local surface wind speed: Statistical modeling and forecasts B Alonzo, R Plougonven, M Mougeot, A Fischer, A Dupré, P Drobinski Renewable Energy: Forecasting and Risk Management: Paris, France, June 7-9 …, 2018 | 14 | 2018 |
| Transfer learning on decision tree with class imbalance L Minvielle, M Atiq, S Peignier, M Mougeot 2019 IEEE 31st international conference on tools with artificial …, 2019 | 13 | 2019 |
| Learning out of leaders M Mougeot, D Picard, K Tribouley Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2012 | 13 | 2012 |
| Learning out of leaders M Mougeot, D Picard, K Tribouley Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2012 | 13 | 2012 |
| A study of image compression with backpropagation M Mougeot, R Azencott, B Angeniol Neurocomputing: Algorithms, Architectures and Applications, 333-336, 1990 | 13 | 1990 |
| Using machine-learning methods to improve surface wind speed from the outputs of a numerical weather prediction model N Goutham, B Alonzo, A Dupré, R Plougonven, R Doctors, L Liao, ... Boundary-Layer Meteorology 179, 133-161, 2021 | 11 | 2021 |
| NMF-based decomposition for anomaly detection applied to vibration analysis M Abdel-Sayed, D Duclos, G Faÿ, J Lacaille, M Mougeot International Journal of Condition Monitoring 6 (3), 73-81, 2016 | 11 | 2016 |
Antoine de MathelinENS Paris-Saclay PhD StudentBestätigte E-Mail-Adresse bei cmla.ens-cachan.fr
