A fast Griffin-Lim algorithm. - Nathanaël Perraudin; Péter Balázs; Peter L. Søndergaard (WASPAA, 2013)

GSPBOX: A toolbox for signal processing on graphs. - Nathanaël Perraudin; Johan Paratte; David I. Shuman; Vassilis Kalofolias; Pierre Vandergheynst; David K. Hammond (CoRR, 2014)

UNLocBoX A matlab convex optimization toolbox using proximal splitting methods. - Nathanaël Perraudin; David I. Shuman; Gilles Puy; Pierre Vandergheynst (CoRR, 2014)

Fast Robust PCA on Graphs. - Nauman Shahid; Nathanaël Perraudin; Vassilis Kalofolias; Pierre Vandergheynst (CoRR, 2015)

Tracking time-vertex propagation using dynamic graph wavelets. - Francesco Grassi; Nathanaël Perraudin; Benjamin Ricaud (GlobalSIP, 2016)

PCA using graph total variation. - Nauman Shahid; Nathanaël Perraudin; Vassilis Kalofolias; Benjamin Ricaud; Pierre Vandergheynst (ICASSP, 2016)

Predicting the evolution of stationary graph signals. - Andreas Loukas; Nathanaël Perraudin (CoRR, 2016)

Audio inpainting with similarity graphs. - Nathanaël Perraudin; Nicki Holighaus; Piotr Majdak; Péter Balázs (CoRR, 2016)

Compressive PCA on Graphs. - Nauman Shahid; Nathanaël Perraudin; Gilles Puy; Pierre Vandergheynst (CoRR, 2016)

Low-Rank Matrices on Graphs: Generalized Recovery & Applications. - Nauman Shahid; Nathanaël Perraudin; Pierre Vandergheynst (CoRR, 2016)

Fast Robust PCA on Graphs. - Nauman Shahid; Nathanaël Perraudin; Vassilis Kalofolias; Gilles Puy; Pierre Vandergheynst (IEEE J. Sel. Top. Signal Process., 2016)

Predicting the evolution of stationary graph signals. - Andreas Loukas; Elvin Isufi; Nathanaël Perraudin (ACSSC, 2017)

Towards stationary time-vertex signal processing. - Nathanaël Perraudin; Andreas Loukas; Francesco Grassi; Pierre Vandergheynst (ICASSP, 2017)

A Time-Vertex Signal Processing Framework. - Francesco Grassi; Andreas Loukas; Nathanaël Perraudin; Benjamin Ricaud (CoRR, 2017)

Compressive Embedding and Visualization using Graphs. - Johan Paratte; Nathanaël Perraudin; Pierre Vandergheynst (CoRR, 2017)

Compressive PCA for Low-Rank Matrices on Graphs. - Nauman Shahid; Nathanaël Perraudin; Gilles Puy; Pierre Vandergheynst (IEEE Trans. Signal Inf. Process. over Networks, 2017)

Stationary Signal Processing on Graphs. - Nathanaël Perraudin; Pierre Vandergheynst (IEEE Trans. Signal Process., 2017)

Designing Gabor windows using convex optimization. - Nathanaël Perraudin; Nicki Holighaus; Peter L. Søndergaard; Péter Balázs (Appl. Math. Comput., 2018)

Improving DNN-based Music Source Separation using Phase Features. - Joachim Muth; Stefan Uhlich; Nathanaël Perraudin; Thomas Kemp; Fabien Cardinaux; Yuki Mitsufuji (CoRR, 2018)

Evaluating GANs via Duality. - Paulina Grnarova; Kfir Y. Levy; Aurélien Lucchi; Nathanaël Perraudin; Thomas Hofmann 001; Andreas Krause 001 (CoRR, 2018)

Inpainting of Long Audio Segments With Similarity Graphs. - Nathanaël Perraudin; Nicki Holighaus; Piotr Majdak; Péter Balázs (IEEE ACM Trans. Audio Speech Lang. Process., 2018)

A Time-Vertex Signal Processing Framework: Scalable Processing and Meaningful Representations for Time-Series on Graphs. - Francesco Grassi; Andreas Loukas; Nathanaël Perraudin; Benjamin Ricaud (IEEE Trans. Signal Process., 2018)

Large Scale Graph Learning From Smooth Signals. - Vassilis Kalofolias; Nathanaël Perraudin (ICLR (Poster), 2019)

Adversarial Generation of Time-Frequency Features with application in audio synthesis. - Andrés Marafioti; Nathanaël Perraudin; Nicki Holighaus; Piotr Majdak (ICML, 2019)

A Domain Agnostic Measure for Monitoring and Evaluating GANs. - Paulina Grnarova; Kfir Y. Levy; Aurélien Lucchi; Nathanaël Perraudin; Ian J. Goodfellow; Thomas Hofmann 001; Andreas Krause 001 (NeurIPS, 2019)

DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications. - Nathanaël Perraudin; Michaël Defferrard; Tomasz Kacprzak; Raphaël Sgier (Astron. Comput., 2019)

DeepSphere: towards an equivariant graph-based spherical CNN. - Michaël Defferrard; Nathanaël Perraudin; Tomasz Kacprzak; Raphaël Sgier (CoRR, 2019)

Discriminative structural graph classification. - Younjoo Seo; Andreas Loukas; Nathanaël Perraudin (CoRR, 2019)

Cosmological N-body simulations: a challenge for scalable generative models. - Nathanaël Perraudin; Ankit Srivastava; Aurélien Lucchi; Tomasz Kacprzak; Thomas Hofmann 001; Alexandre Réfrégier (CoRR, 2019)

Stationary time-vertex signal processing. - Andreas Loukas; Nathanaël Perraudin (EURASIP J. Adv. Signal Process., 2019)

A Context Encoder For Audio Inpainting. - Andrés Marafioti; Nathanaël Perraudin; Nicki Holighaus; Piotr Majdak (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

Forecasting Time Series With VARMA Recursions on Graphs. - Elvin Isufi; Andreas Loukas; Nathanaël Perraudin; Geert Leus (IEEE Trans. Signal Process., 2019)

DeepSphere: a graph-based spherical CNN. - Michaël Defferrard; Martino Milani; Frédérick Gusset; Nathanaël Perraudin (ICLR, 2020)

GACELA - A generative adversarial context encoder for long audio inpainting. - Andrés Marafioti; Piotr Majdak; Nicki Holighaus; Nathanaël Perraudin (CoRR, 2020)

Scalable Graph Networks for Particle Simulations. - Karolis Martinkus; Aurélien Lucchi; Nathanaël Perraudin (AAAI, 2021)

A data acquisition setup for data driven acoustic design. - Romana Rust; Achilleas Xydis; Kurt Heutschi; Nathanaël Perraudin; Gonzalo Casas; Chaoyu Du; Jürgen Strauss; Kurt Eggenschwiler; Fernando Pérez-Cruz; Fabio Gramazio; Matthias Kohler (CoRR, 2021)

Emulation of Cosmological Mass Maps with Conditional Generative Adversarial Networks. - Nathanaël Perraudin; Sandro Marcon; Aurélien Lucchi; Tomasz Kacprzak (Frontiers Artif. Intell., 2021)

GACELA: A Generative Adversarial Context Encoder for Long Audio Inpainting of Music. - Andrés Marafioti; Piotr Majdak; Nicki Holighaus; Nathanaël Perraudin (IEEE J. Sel. Top. Signal Process., 2021)

SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators. - Karolis Martinkus; Andreas Loukas; Nathanaël Perraudin; Roger Wattenhofer (ICML, 2022)

What You See is What You Classify: Black Box Attributions. - Steven Stalder; Nathanaël Perraudin; Radhakrishna Achanta; Fernando Pérez-Cruz; Michele Volpi (NeurIPS, 2022)

Diffusion Models for Graphs Benefit From Discrete State Spaces. - Kilian Konstantin Haefeli; Karolis Martinkus; Nathanaël Perraudin; Roger Wattenhofer (CoRR, 2022)

An evaluation of deep learning models for predicting water depth evolution in urban floods. - Stefania Russo; Nathanaël Perraudin; Steven Stalder; Fernando Pérez-Cruz; João Paulo Leitão; Guillaume Obozinski; Jan Dirk Wegner (CoRR, 2023)

Efficient and Scalable Graph Generation through Iterative Local Expansion. - Andreas Bergmeister; Karolis Martinkus; Nathanaël Perraudin; Roger Wattenhofer (ICLR, 2024)

Efficient algorithms for regularized Poisson Non-negative Matrix Factorization. - Nathanaël Perraudin; Adrien Teutrie; Cécile Hébert; Guillaume Obozinski (CoRR, 2024)

High Resolution Seismic Waveform Generation using Denoising Diffusion. - Andreas Bergmeister; Kadek Hendrawan Palgunadi; Andrea Bosisio; Laura Ermert; Maria Koroni; Nathanaël Perraudin; Simon Dirmeier; Men-Andrin Meier (CoRR, 2024)

Coarse-to-Fine Text-to-Music Latent Diffusion. - Luca A. Lanzendörfer; Tongyu Lu; Nathanaël Perraudin; Dorien Herremans; Roger Wattenhofer (ICASSP, 2025)

Bootstrapping Language-Audio Pre-training for Music Captioning. - Luca A. Lanzendörfer; Constantin Pinkl; Nathanaël Perraudin; Roger Wattenhofer (ICASSP, 2025)