nicolas tremblay
Cited by
Cited by
Graph wavelets for multiscale community mining
N Tremblay, P Borgnat
IEEE Transactions on Signal Processing 62 (20), 5227-5239, 2014
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
Compressive spectral clustering
N Tremblay, G Puy, R Gribonval, P Vandergheynst
Proceedings of the 33 rd International Conference on Machine Learning …, 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, ...
2013 ACM/IEEE International Conference on Information Processing in Sensor …, 2013
Subgraph-based filterbanks for graph signals
N Tremblay, P Borgnat
IEEE Transactions on Signal Processing 64 (15), 3827-3840, 2016
Design of graph filters and filterbanks
N Tremblay, P Gonçalves, P Borgnat
Cooperative and Graph Signal Processing, 299-324, 2018
Compressive K-means
N Keriven, N Tremblay, Y Traonmilin, R Gribonval
2017 IEEE International Conference on Acoustics, Speech and Signal …, 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, 267-284, 2013
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
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
Approximating spectral clustering via sampling: a review
N Tremblay, A Loukas
Sampling Techniques for Supervised or Unsupervised Tasks, 129-183, 2020
Graph sampling with determinantal processes
N Tremblay, PO Amblard, S Barthelmé
2017 25th European Signal Processing Conference (EUSIPCO), 1674-1678, 2017
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
Probing slow dynamics of consolidated granular multicomposite materials by diffuse acoustic wave spectroscopy
N Tremblay, É Larose, V Rossetto
The Journal of the Acoustical Society of America 127 (3), 1239-1243, 2010
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
Determinantal Point Processes for Coresets.
N Tremblay, S Barthelmé, PO Amblard
J. Mach. Learn. Res. 20, 168:1-168:70, 2019
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
Multiscale community mining in networks using spectral graph wavelets
N Tremblay, P Borgnat
21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013
Mining anomalous electricity consumption using ensemble empirical mode decomposition
R Fontugne, N Tremblay, P Borgnat, P Flandrin, H Esaki
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
Independent re-analysis of alleged mind-matter interaction in double-slit experimental data
N Tremblay
PloS one 14 (2), e0211511, 2019
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