| PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures M Carrière, F Chazal, Y Ike, T Lacombe, M Royer, Y Umeda International Conference on Artificial Intelligence and Statistics, 2786-2796, 2019 | 198* | 2019 |
| Adaptive clustering through semidefinite programming M Royer Advances in Neural Information Processing Systems, 1795-1803, 2017 | 42 | 2017 |
| Model assisted variable clustering: minimax-optimal recovery and algorithms F Bunea, C Giraud, X Luo, M Royer, N Verzelen The Annals of Statistics 48 (1), 111-137, 2020 | 26 | 2020 |
| ATOL: Measure Vectorisation for Automatic Topologically-Oriented Learning M Royer, F Chazal, C Levrard, Y Ike, Y Umeda International Conference on Artificial Intelligence and Statistics, 2020 | 24 | 2020 |
| PECOK: a convex optimization approach to variable clustering F Bunea, C Giraud, M Royer, N Verzelen arXiv preprint arXiv:1606.05100, 2016 | 21 | 2016 |
| Model assisted variable clustering: minimax-optimal recovery and algorithms F Bunea, C Giraud, X Luo, M Royer, N Verzelen arXiv preprint arXiv:1508.01939, 2015 | 12 | 2015 |
| Persistence representations P Dlotko, M Carriere, M Royer GUDHI User and Reference Manual 1, 2021 | 11 | 2021 |
| Clustering of measures via mean measure quantization F Chazal, C Levrard, M Royer Electronic Journal of Statistics 15 (1), 2060-2104, 2021 | 10* | 2021 |
| Latent model-based clustering for biological discovery X Bing, F Bunea, M Royer, J Das iScience 14, 125-135, 2019 | 7 | 2019 |
| Optimalité statistique du partitionnement par l'optimisation convexe M Royer Université Paris-Saclay (ComUE), 2018 | 1* | 2018 |
| Topological Analysis for Detecting Anomalies (TADA) in Time Series F Chazal, C Levrard, M Royer | | 2024 |
Frederic ChazalINRIA Saclay - Ile de France在 inria.fr 的电子邮件经过验证
