Michaël Defferrard | DeepAI

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Featured Co-authors

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∙ 11/23/2021

ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups

We introduce ChebLieNet, a group-equivariant method on (anisotropic) man...

3 Hugo Aguettaz, et al. ∙

∙ 04/13/2021

Learning to recover orientations from projections in single-particle cryo-EM

A major challenge in single-particle cryo-electron microscopy (cryo-EM) ...

5 Jelena Banjac, et al. ∙

∙ 12/30/2020

DeepSphere: a graph-based spherical CNN

Designing a convolution for a spherical neural network requires a delica...

0 Michaël Defferrard, et al. ∙

∙ 10/07/2020

Simplicial Neural Networks

We present simplicial neural networks (SNNs), a generalization of graph ...

45 Stefania Ebli, et al. ∙

∙ 04/08/2019

DeepSphere: towards an equivariant graph-based spherical CNN

Spherical data is found in many applications. By modeling the discretize...

0 Michaël Defferrard, et al. ∙

∙ 10/29/2018

DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications

Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learn...

0 Nathanaël Perraudin, et al. ∙

∙ 03/13/2018

Learning to Recognize Musical Genre from Audio

We here summarize our experience running a challenge with open data for ...

0 Michaël Defferrard, et al. ∙

∙ 12/22/2016

Structured Sequence Modeling with Graph Convolutional Recurrent Networks

This paper introduces Graph Convolutional Recurrent Network (GCRN), a de...

0 Youngjoo Seo, et al. ∙

∙ 06/30/2016

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

In this work, we are interested in generalizing convolutional neural net...

0 Michaël Defferrard, et al. ∙

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