Michaël Defferrard
EPFL STI IEL LTS2
ELE 227 (Bâtiment ELE)
Station 11
CH-1015 Lausanne
Unité: EDEE
Compétences
Machine Learning
Data Science
Neural Networks
Graph Signal Processing
Data Science
Neural Networks
Graph Signal Processing
Publications
Infoscience
All publications
[12]
L. Zampieri : Geometric Deep Learning for Volumetric Computational Fluid Dynamics ; 2019-06-21.
[11]
F. Gusset : Spherical Convolutionnal Neural Networks: Empirical Analysis of SCNNs ; 2019-06-21.
[10]
C. Gallay : Exploiting symmetries (in images) with graph neural networks ; 2019-06-21.
[9]
N. Perraudin; M. Defferrard; T. Kacprzak; R. Sgier : DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications; Astronomy And Computing. 2019-04-01. DOI : 10.1016/j.ascom.2019.03.004.
[8]
M. Milani : Graph Laplacians for Rotation Equivariant Convolutional Neural Networks ; 2019.
[7]
A. Cherqui : Deep learning on graph for semantic segmentation of point cloud ; 2018-07-02.
[6]
Y. Seo; M. Defferrard; P. Vandergheynst; X. Bresson : Structured Sequence Modeling with Graph Convolutional Recurrent Networks. 2017.
[5]
M. Defferrard; K. Benzi; P. Vandergheynst; X. Bresson : FMA: A Dataset For Music Analysis. 2017. 18th International Society for Music Information Retrieval Conference, Suzhou, China, October 23-28, 2017.
[4]
M. Defferrard; X. Bresson; P. Vandergheynst : Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. 2016. Advances in Neural Information Processing Systems 29, Barcelona, Spain, December 5-10, 2016.
[3]
M. Defferrard : Structured Auto-Encoder with application to Music Genre Recognition ; 2015.
[2]
M. Defferrard : LiveMesh, a tool for real-time rendering of neuronal cells from morphologies ; 2014.
[1]
M. Defferrard : Graph-based Image Inpainting ; 2014.