mdeff Goto Github PK
Name: Michaël Defferrard
Type: User
Company: EPFL
Bio: Research on machine learning and graphs. Open science, source, data.
Twitter: m_deff
Location: Switzerland
Blog: https://deff.ch
Michaël Defferrard's Projects
atcsim
Air Traffic Control simulation, a C++11 learning experience
cnn_graph
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
cv
Curriculum Vitae
dlaudio
Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (code)
dlaudio_report
Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (report)
dlaudio_results
Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (results)
dotfiles
my dotfiles
fma
FMA: A Dataset For Music Analysis
giin
Graph-based Image Inpainting
gsp-summer-school-2016
Organization of a Graph Signal Processing Summer School
learning-from-graphs-webconf2021
Learning from Graphs: From Mathematical Principles to Practical Tools
ntds_2016
Material for the EPFL master course "A Network Tour of Data Science", edition 2016.
ntds_2017
Material for the EPFL master course "A Network Tour of Data Science", edition 2017.
ntds_2018
Material for the EPFL master course "A Network Tour of Data Science", edition 2018.
ntds_2019
Material for the EPFL master course "A Network Tour of Data Science", edition 2019.
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
paper-cheblienet
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups
paper-cnn-graph-nips2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
paper-cnn-graph-recurrent-iclr2017
Structured Sequence Modeling with Graph Convolutional Recurrent Networks
paper-cryoem-orientation-recovery
Learning to recover orientations from projections in single-particle cryo-EM
paper-fma-challenge-webconf2018
Learning to Recognize Musical Genre from Audio, Challenge Overview
paper-fma-ismir2017
FMA: A Dataset For Music Analysis
pygsp_tutorial_graphsip
Graph signal processing tutorial, presented at the GraphSiP summer school.
python_tour_of_data_science
A Python Tour of Data Science
saga
Mini-batch and distributed SAGA
srfsp
Super-resolution for mass spectrometry
terrain
OpenGL generated scene
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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