GuillaumeStaermanML

Postdoctoral researcher in the MIND (ex-Parietal) team in INRIA Saclay

INRIA, SaclayParis, France

Pinned Repositories

ACHD
Source code for the AISTATS 2020 paper "The Area of the Convex Hull of Sampled Curves".
Language:C5 2 12
AIIRW
Source code of Electronic Journal of Statistics (2023) paper: the Affine-Invariant Integrated Rank-Weighted depth
Language:Jupyter Notebook6 1 00
alphacsc
Convolution dictionary learning for time-series
Language:Python00
DRPM
Source code of TMLR 2024 paper: the Depth-Trimmed Regions based Pseudo-Metric
Language:Python40
FIF
Source code for the ACML 2019 paper "Functional Isolation Forest".
Language:Jupyter Notebook20 3 52
fugw
Scalable python GPU solvers for FUGW optimal transport problems
Language:Python0 0 00
guillaumestaermanml.github.io
Website
Language:Python0 1 00
MoM-Wasserstein
Source code of the AISTATS 2021 Paper: "When OT meets MoM: a robust estimation of the Wasserstein distance".
Language:Python8 1 02
momentumnet
Drop-in replacement for any ResNet with a significantly reduced memory footprint and better representation capabilities
Language:Python0 0 00
FaDIn
Documentation
Language:Python5 4 21

GuillaumeStaermanML/FIF
Source code for the ACML 2019 paper "Functional Isolation Forest".
Language:Jupyter Notebook20 3 52
GuillaumeStaermanML/MoM-Wasserstein
Source code of the AISTATS 2021 Paper: "When OT meets MoM: a robust estimation of the Wasserstein distance".
Language:Python8 1 02
GuillaumeStaermanML/AIIRW
Source code of Electronic Journal of Statistics (2023) paper: the Affine-Invariant Integrated Rank-Weighted depth
Language:Jupyter Notebook6 1 00
GuillaumeStaermanML/ACHD
Source code for the AISTATS 2020 paper "The Area of the Convex Hull of Sampled Curves".
Language:C5 2 12
GuillaumeStaermanML/DRPM
Source code of TMLR 2024 paper: the Depth-Trimmed Regions based Pseudo-Metric
Language:Python40
GuillaumeStaermanML/alphacsc
Convolution dictionary learning for time-series
Language:Python00
GuillaumeStaermanML/fugw
Scalable python GPU solvers for FUGW optimal transport problems
Language:Python0 0 00
GuillaumeStaermanML/guillaumestaermanml.github.io
Website
Language:Python0 1 00
GuillaumeStaermanML/momentumnet
Drop-in replacement for any ResNet with a significantly reduced memory footprint and better representation capabilities
Language:Python0 0 00
GuillaumeStaermanML/tick
Module for statistical learning, with a particular emphasis on time-dependent modelling