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Nathanael Perraudin
Nathanael Perraudin
Swiss Data Science Center - EPFL and ETH Zürich
Verified email at ethz.ch - Homepage
Title
Cited by
Cited by
Year
GSPBOX: A toolbox for signal processing on graphs
N Perraudin, J Paratte, D Shuman, L Martin, V Kalofolias, ...
arXiv preprint arXiv:1408.5781, 2014
3792014
Stationary signal processing on graphs
N Perraudin, P Vandergheynst
IEEE Transactions on Signal Processing 65 (13), 3462-3477, 2017
2692017
A fast Griffin-Lim algorithm
N Perraudin, P Balazs, PL Sondergaard
2013 IEEE Workshop on Applications of Signal Processing to Audio and …, 2013
2242013
Deepsphere: Efficient spherical convolutional neural network with healpix sampling for cosmological applications
N Perraudin, M Defferrard, T Kacprzak, R Sgier
Astronomy and Computing 27, 130-146, 2019
2142019
A Time-Vertex Signal Processing Framework: Scalable Processing and Meaningful Representations for Time-Series on Graphs
F Grassi, A Loukas, N Perraudin, B Ricaud
IEEE Transactions on Signal Processing 66 (3), 817 - 829, 2017
1972017
Fast robust pca on graphs
N Shahid, N Perraudin, V Kalofolias, P Vandergheynst
IEEE Journal of Selected Topics in Signal Processing 10 (4), 740-756, 2016
1422016
Forecasting time series with VARMA recursions on graphs
E Isufi, A Loukas, N Perraudin, G Leus
IEEE Transactions on Signal Processing 67 (18), 4870-4885, 2019
1242019
DeepSphere: a graph-based spherical CNN
M Defferrard, M Milani, F Gusset, N Perraudin
Eighth International Conference on Learning Representations (ICLR), 2020
1112020
Large scale graph learning from smooth signals
V Kalofolias, N Perraudin
ICLR, International Conference on Learning Representations, 2019
982019
UNLocBoX: A MATLAB convex optimization toolbox for proximal-splitting methods
N Perraudin, V Kalofolias, D Shuman, P Vandergheynst
arXiv preprint arXiv:1402.0779, 2014
962014
Adversarial Generation of Time-Frequency Features with application in audio synthesis
A Marafioti, N Holighaus, N Perraudin, P Majdak
36th International Conference on Machine Learning (ICML) 97, 4352--4362, 2019
952019
Global and local uncertainty principles for signals on graphs
N Perraudin, B Ricaud, D Shuman, P Vandergheynst
APSIPA Transactions on Signal and Information 7, 2018
882018
A context encoder for audio inpainting
A Marafioti, N Perraudin, N Holighaus, P Majdak
IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (12 …, 2019
852019
Accelerated filtering on graphs using lanczos method
A Susnjara, N Perraudin, D Kressner, P Vandergheynst
arXiv preprint arXiv:1509.04537, 2015
722015
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
K Martinkus, A Loukas, N Perraudin, R Wattenhofer
39th International Conference on Machine Learning 162, 15159--15179, 2022
712022
Stationary time-vertex signal processing
A Loukas, N Perraudin
EURASIP journal on advances in signal processing 2019 (1), 1-19, 2019
612019
Pygsp: Graph signal processing in python
M Defferrard, L Martin, R Pena, N Perraudin
URL https://github. com/epfl-lts2/pygsp, 2017
612017
Towards stationary time-vertex signal processing
N Perraudin, A Loukas, F Grassi, P Vandergheynst
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
582017
GACELA: A generative adversarial context encoder for long audio inpainting of music
A Marafioti, P Majdak, N Holighaus, N Perraudin
IEEE Journal of Selected Topics in Signal Processing 15 (1), 120-131, 2020
542020
Diffusion models for graphs benefit from discrete state spaces
KK Haefeli, K Martinkus, N Perraudin, R Wattenhofer
LOG 2022, The First Learning on Graphs Conference, 2022
532022
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