| Random sampling of bandlimited signals on graphs G Puy, N Tremblay, R Gribonval, P Vandergheynst Applied and Computational Harmonic Analysis 44 (2), 446-475, 2018 | 201 | 2018 |
| Graph wavelets for multiscale community mining N Tremblay, P Borgnat IEEE Transactions on Signal Processing 62 (20), 5227-5239, 2014 | 196 | 2014 |
| Compressive spectral clustering N Tremblay, G Puy, R Gribonval, P Vandergheynst Proceedings of the 33 rd International Conference on Machine Learning …, 2016 | 139 | 2016 |
| Strip, bind, and search: a method for identifying abnormal energy consumption in buildings R Fontugne, J Ortiz, N Tremblay, P Borgnat, P Flandrin, K Fukuda, ... Proceedings of the 12th international conference on Information processing …, 2013 | 111 | 2013 |
| Subgraph-based filterbanks for graph signals N Tremblay, P Borgnat IEEE Transactions on Signal Processing 64 (15), 3827-3840, 2016 | 102 | 2016 |
| Design of graph filters and filterbanks N Tremblay, P Gonçalves, P Borgnat Cooperative and Graph Signal Processing, 299-324, 2018 | 95 | 2018 |
| Fourier could be a data scientist: From graph Fourier transform to signal processing on graphs B Ricaud, P Borgnat, N Tremblay, P Gonçalves, P Vandergheynst Comptes Rendus. Physique 20 (5), 474-488, 2019 | 76 | 2019 |
| Compressive K-means N Keriven, N Tremblay, Y Traonmilin, R Gribonval 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 73 | 2017 |
| Approximate fast graph Fourier transforms via multilayer sparse approximations L Le Magoarou, R Gribonval, N Tremblay IEEE transactions on Signal and Information Processing over Networks 4 (2 …, 2017 | 67 | 2017 |
| A dynamical network view of lyon’s vélo’v shared bicycle system P Borgnat, C Robardet, P Abry, P Flandrin, JB Rouquier, N Tremblay Dynamics On and Of Complex Networks, Volume 2: Applications to Time-Varying …, 2013 | 61 | 2013 |
| Approximating spectral clustering via sampling: a review N Tremblay, A Loukas Sampling Techniques for Supervised or Unsupervised Tasks, 129-183, 2020 | 58 | 2020 |
| Multiscale anisotropic texture analysis and classification of photographic prints: Art scholarship meets image processing algorithms P Abry, SG Roux, H Wendt, P Messier, AG Klein, N Tremblay, P Borgnat, ... IEEE Signal Processing Magazine 32 (4), 18-27, 2015 | 49 | 2015 |
| Graph sampling with determinantal processes N Tremblay, PO Amblard, S Barthelmé 2017 25th European signal processing conference (EUSIPCO), 1674-1678, 2017 | 48 | 2017 |
| Probing slow dynamics of consolidated granular multicomposite materials by diffuse acoustic wave spectroscopy N Tremblay, E Larose, V Rossetto The Journal of the Acoustical Society of America 127 (3), 1239-1243, 2010 | 44 | 2010 |
| Revisiting the bethe-hessian: improved community detection in sparse heterogeneous graphs L Dall'Amico, R Couillet, N Tremblay Advances in neural information processing systems 32, 2019 | 40 | 2019 |
| Accelerated spectral clustering using graph filtering of random signals N Tremblay, G Puy, P Borgnat, R Gribonval, P Vandergheynst 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 37 | 2016 |
| Determinantal point processes for coresets N Tremblay, S Barthelmé, PO Amblard Journal of Machine Learning Research 20 (168), 1-70, 2019 | 35 | 2019 |
| Multiscale community mining in networks using spectral graph wavelets N Tremblay, P Borgnat 21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013 | 25 | 2013 |
| Spatiotemporal reorganization of corticostriatal networks encodes motor skill learning N Badreddine, G Zalcman, F Appaix, G Becq, N Tremblay, F Saudou, ... Cell reports 39 (1), 2022 | 24 | 2022 |
| A unified framework for spectral clustering in sparse graphs L Dall'Amico, R Couillet, N Tremblay Journal of Machine Learning Research 22 (217), 1-56, 2021 | 22 | 2021 |
Pierre BorgnatResearch Director, CNRS, ENS Lyon, Physics Laboratory (LP ENSL)在 ens-lyon.fr 的电子邮件经过验证
