Personal Website

L-System fractal with rules: \begin{align*}F &\rightarrow FF \\ X & \rightarrow F+[[X]-X]-F[-FX]+X)\end{align*}

Publications

  • 2021
    • Collin, F., Durif, G., Raynal, L., Lombaert, E., Gautier, M., Vitalis, R., Marin, J.-M., & Estoup, A. (2021). Extending Approximate Bayesian Computation with Supervised Machine Learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest. Molecular Ecology Resources, 21(8), 2598–2613. https://doi.org/10.1111/1755-0998.13413
    • Charlier, B., Feydy, J., Glaunès, J., Collin, F.-D., & Durif, G. (2021). Kernel Operations on the GPU, with Autodiff,without Memory Overflows. Journal of Machine Learning Research, 22(74), 1–6. https://doi.org/10.48550/arXiv.2004.11127
  • 2012
    • Benbouzid, D., Busa-Fekete, R., Casagrande, N., Collin, F.-D., & Kégl, B. (2012). Multiboost: a multi-purpose boosting package. Journal of Machine Learning Research, 13, 549–553. https://hal.in2p3.fr/in2p3-00698455
  • 2020
    • Collin, F.-D., Estoup, A., Marin, J.-M., & Raynal, L. (2020). Bringing ABC inference to the machine learning realm : AbcRanger, an optimized random forests library for ABC. JOBIM 2020, 2020. https://hal.science/hal-02910067
  • 2019
    • Collin, F.-D., Estoup, A., Marin, J.-M., & Raynal, L. (2019). AbcRanger, A fast and scalable random forest library for ABC model choice and parameter estimation. JCAD 2019. https://hal.science/hal-04207225
  • 2018
    • Virgoulay, T., Leblois, R., Dehne Garcia, A., & Collin, F. D. (2018). Développement et optimisation d’un outil de simulation en C++ de données génomiques en populations spatialisées (p. 366 p.). Société Française de Bio-Informatique (SFBI). FRA. GdR 3003 Bioinformatique Moléculaire (GdR BiM), FRA. Institut Français de Bioinformatique (IFB), FRA. Aix Marseille Université (AMU), FRA. Institut National de la Santé et de la Recherche Médicale (INSERM), FRA. Centre National de la Recherche Scientifique (CNRS), FRA. https://hal.inrae.fr/hal-02733797
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Teaching

Montpellier, France, 2023 CNRS

Introduction to Machine Learning and Deep Learning

joint work with Ghislain Durif and Claudia Restrepo-Ortiz
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Montpellier, France, 2019 Paul Valéry University

Sequences in Deep Learning with pytorch

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Montpellier, France, 2018 Paul Valéry University

General introduction to Deep Learning

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Montpellier, France, 2021-2023 Paul Valéry University

High Performance Computing and Advanced programming

joint work with Ghislain Durif in 2021
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Presentations

Bordeaux, France, May 31, 2024

Workshop on reproducible research

Reproducible research, past and future, with Computo and Quarto (presentation), and a hands-on introduction to Quarto with the Computo template (workshop)

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Montpellier, France, Oct 24, 2023

ChatGPT, Myths and Realities

A (very) general in troduction to LLMs and Deep Learning

In collaboration with Tanguy Lefort
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Montpellier, France, Jan 13, 2020

AbcRanger

A brief introduction to the AbcRanger library and bayesian methologies for ABC model choice and parameter estimation.

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Toulouse, France, Oct 15, 2019

L’IA avec .net core et F#

An overview of the .net core ecosystem for machine learning and data science, with a focus on F# and ML.NET.

In French. The notebook infrastructure is outdated.
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Lyon, France, Sep 20, 2019

Culture Fonctionnelle: F#

A presentation of the F# language for the 2019 In2p3’s Computer School on Functional Programming.

In French. The notebook infrastructure is outdated.
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