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No. | Title | Year | Type |
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003 |
Designing Gabor windows using convex optimization
Nathanael Perraudin, Nicki Hollighaus, Peter L. Sondergaard, Peter Balazs
Elsevier, Applied Mathematics and Computation
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2014
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Article |
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006 |
Fast Robust PCA on Graphs
Nauman Shahid, Nathanael Perraudin, Vassilis Kalofolias, Pierre Vandergheynst
IEEE Journal of Selected Topics in Signal Processing
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Code
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2015
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Article |
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008 |
Stationary signal processing on graphs
Nathanael Perraudin, Pierre Vandergheynst
IEEE Transactions on Signal Processing
slides
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Code
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2016
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Article |
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009 |
Compressive pca for low-rank matrices on graphs
Nauman Shahid, Nathanael Perraudin, Gilles Puy, Pierre Vandergheynst
IEEE transactions on Signal and Information Processing over Networks
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2016
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Article |
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010 |
Global and Local Uncertainty Principles for Signals on Graphs
Nathanael Perraudin, Benjamin Ricaud, David Shuman, Pierre Vandergheynst
Cambridge University Press, APSIPA Transactions on Signal and Information Processing
poster
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Code
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2016
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Article |
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016 |
Inpainting of long audio segments with similarity graphs
Nathanael Perraudin, Nicki Hollighaus, Piotr Majdak, Peter Balazs
IEEE/ACM Transactions on Audio, Speech, and Language Processing
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Code
Demo
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2018
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Article |
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017 |
Stationary time-vertex signal processing
Andreas Loukas, Nathanael Perraudin
EURASIP Journal on Advances in Signal Processing
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Reproducible research
Webpage
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2018
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Article |
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018 |
Large Scale Graph Learning from Smooth Signals
Vassilis Kalofolias, Nathanael Perraudin
ICLR 2019, Seventh International Conference on Learning Representations
poster
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2018
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Article |
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020 |
A Time-Vertex Signal Processing Framework
Francesco Grassi, Andreas Loukas, Nathanael Perraudin, Benjamin Ricaud
IEEE Transactions on Signal Processing
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Reproducible research
Webpage
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2017
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Article |
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021 |
Improving DNN-based music source separation using phase features
Joachim Muth, Stefan Uhlich, Nathanael Perraudin, Thomas Kemp, Fabien Cardinaux, Yuki Mitsufuji
Joint Workshop on Machine Learning for Music at ICML, IJCAI/ECAI and AAMAS, 201
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2018
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Article |
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023 |
DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
Nathanael Perraudin, Michaël Defferrard, Tomasz Kacprzak, Raphaël Sgier
Astronomy and Computing, Elsevier
poster
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2018
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Article |
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024 |
Forecasting Time Series with VARMA Recursions on Graphs
Elvin Isufifi, Andreas Loukas, Nathanael Perraudin, Geert Leus
IEEE Transactions on Signal Processing
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2018
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Article |
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025 |
A domain agnostic measure for monitoring and evaluating GANs
Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi, Nathanael Perraudin, Thomas Hofmann, Andreas Krause
Advances in Neural Information Processing Systems (Neurips), 2019
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2019
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Article |
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026 |
A context encoder for audio inpainting
Andrés Marafioti, Nathanael Perraudin, Nicki Hollighaus, Piotr Majdak
IEEE/ACM Transactions on Audio, Speech, and Language Processin
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Code
Example
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2018
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Article |
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027 |
DeepSphere: a graph-based spherical CNN with approximate equivariance
Michaël Defferrard, Nathanael Perraudin, Tomasz Kacprzak, Raphaël Sgier
Representation Learning on Graphs and Manifolds, ICLR 2019 Workshop
poster
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Code
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2018
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Article |
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028 |
Adversarial Generation of Time-Frequency Features with application in audio synthesis
Andrés Marafioti, Nicki Hollighaus, Nathanael Perraudin, Piotr Majdak
International Conference on Machine Learning (ICML), 2019
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Code
Example
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2019
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Article |
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029 |
Cosmological N-body simulations: a challenge for scalable generative models
Nathanael Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
Computational Astrophysics and Cosmology
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Code
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2019
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Article |
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030 |
DeepSphere: a graph-based spherical CNN
Michaël Defferrard, Martino Milani, Frédérick Gusset, Nathanael Perraudin
International Conference on Learning Representations (ICLR), 2020
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Code
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2020
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Article |
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031 |
Emulation of cosmological mass maps with conditional generative adversarial networks
Nathanael Perraudin, Sandro Marcon, Aurelien Lucchi, Tomasz Kacprzak
Machine Learning and the Physical Sciences Workshop (Neurips 2019)
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2019
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Article |
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032 |
GACELA--A generative adversarial context encoder for long audio inpainting
Andrés Marafioti, Nicki Hollighaus, Piotr Majdak, Nathanael Perraudin
In review
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Code
Example
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2020
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Article |
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014 |
Towards stationary time-vertex signal processing
Nathanael Perraudin, Andreas Loukas, Francesco Grassi, Pierre Vandergheynst
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
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2016
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Conference Paper |
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001 |
Gabor dual windows using convex optimization
Nathanael Perraudin, Nicki Hollighaus, Peter L. Sondergaard, Peter Balazs
Proceeedings of the 10th International Conference on Sampling theory and Applications (SAMPTA 2013)
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Code
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2013
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Conference paper |
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002 |
A fast Griffin-Lim algorithm
Nathanael Perraudin, Peter L. Sondergaard, Peter Balazs
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
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Code
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2013
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Conference paper |
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007 |
PCA using Graph Total variation
Nauman Shahid, Nathanael Perraudin, Vassilis Kalofolias, Benjamin Ricaud, Pierre Vandergheynst
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Code
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2015
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Conference paper |
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013 |
Tracking Time-Vertex Propagation using Dynamic Graph Wavelets
Francesco Grassi, Nathanael Perraudin, Benjamin Ricaud
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
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2017
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Conference paper |
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015 |
Predicting the evolution of stationary graph signals
Andreas Loukas, Elvin Isufifi, Nathanael Perraudin
51st Asilomar Conference on Signals, Systems, and Computers, 2017
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2016
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Conference paper |
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004 |
The UNLocBoX: A Matlab convex optimization toolbox using proximal splitting methods
Nathanael Perraudin, David Shuman, Gilles Puy, Pierre Vandergheynst
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Website
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2013
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Technical report |
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005 |
Accelerated filtering on graphs using Lanczos method
Ana Susnjara, Nathanael Perraudin, Daniel Kressner, Pierre Vandergheynst
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Code
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2015
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Technical report |
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011 |
GSPBOX: A toolbox for signal processing on graphs
Nathanael Perraudin, Johan Paratte, David Shuman, Lionel Martin, Vassilis Kalofolias, Pierre Vandergheynst, David K. Hammond
poster
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Website
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2016
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Technical report |
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012 |
Low-Rank Matrices on Graphs: Generalized Recovery & Applications
Nauman Shahid, Nathanael Perraudin, Pierre Vandergheynst
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2016
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Technical report |
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019 |
Graph-based structures in Data Science: Fundamental limits and applications to Machine Learning
Nathanael Perraudin
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Reproducible research
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2017
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Thesis |
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