Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. - Michaël Defferrard; Xavier Bresson; Pierre Vandergheynst (NIPS, 2016)

FMA: A Dataset for Music Analysis. - Michaël Defferrard; Kirell Benzi; Pierre Vandergheynst; Xavier Bresson (ISMIR, 2017)

FMA: A Dataset For Music Analysis. - Michaël Defferrard; Kirell Benzi; Pierre Vandergheynst; Xavier Bresson (UCI Machine Learning Repository, 2017)

Structured Sequence Modeling with Graph Convolutional Recurrent Networks. - Youngjoo Seo; Michaël Defferrard; Pierre Vandergheynst; Xavier Bresson (ICONIP (1), 2018)

Learning to Recognize Musical Genre from Audio: Challenge Overview. - Michaël Defferrard; Sharada P. Mohanty; Sean F. Carroll; Marcel Salathé (WWW (Companion Volume), 2018)

Learning to Recognize Musical Genre from Audio. - Michaël Defferrard; Sharada P. Mohanty; Sean F. Carroll; Marcel Salathé (CoRR, 2018)

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)

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

Simplicial Neural Networks. - Stefania Ebli; Michaël Defferrard; Gard Spreemann (CoRR, 2020)

Connectome spectral analysis to track EEG task dynamics on a subsecond scale. - Katharina Glomb; Joan Rué Queralt; David Pascucci; Michaël Defferrard; Sébastien Tourbier; Margherita Carboni; Maria Rubega; Serge Vulliémoz; Gijs Plomp; Patric Hagmann (NeuroImage, 2020)

Learning to recover orientations from projections in single-particle cryo-EM. - Jelena Banjac; Laurène Donati; Michaël Defferrard (CoRR, 2021)

ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups. - Hugo Aguettaz; Erik J. Bekkers; Michaël Defferrard (CoRR, 2021)

RosettaSurf - A surface-centric computational design approach. - Andreas Scheck; Stéphane Rosset; Michaël Defferrard; Andreas Loukas; Jaume Bonet; Pierre Vandergheynst; Bruno E. Correia (PLoS Comput. Biol., 2022)

fma-small-tfds. - Michaël Defferrard; Kirell Benzi; Pierre Vandergheynst; Xavier Bresson (Zenodo, 2023)

DE-HNN: An effective neural model for Circuit Netlist representation. - Zhishang Luo; Truong Son Hy; Puoya Tabaghi; Michaël Defferrard; Elahe Rezaei; Ryan Carey; W. Rhett Davis; Rajeev Jain; Yusu Wang 001 (AISTATS, 2024)

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. - Natasha Butt; Blazej Manczak; Auke J. Wiggers; Corrado Rainone; David W. Zhang; Michaël Defferrard; Taco Cohen (ICML, 2024)

DE-HNN: An effective neural model for Circuit Netlist representation. - Zhishang Luo; Truong Son Hy; Puoya Tabaghi; Donghyeon Koh; Michaël Defferrard; Elahe Rezaei; Ryan Carey; W. Rhett Davis; Rajeev Jain; Yusu Wang 001 (CoRR, 2024)

NeuroSteiner: A Graph Transformer for Wirelength Estimation. - Sahil Manchanda; Dana Kianfar; Markus Peschl; Romain Lepert; Michaël Defferrard (CoRR, 2024)