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sylvaincom/README.md

Hi there, I'm Sylvain Combettes 👋

Since September 2024, I have been a Machine Learning Product Engineer at Probabl, the official brand operator of scikit-learn. I contribute to skore, the scikit-learn modeling companion.

Previously, I was a PhD student, at Ecole Normale Supérieure Paris-Saclay (France), where I worked on machine learning applied to time series. More precisely, my research focused on symbolic representation for time series, as well as distance measures on them.

📂 I've recently (Dec 2024) started to organize my GitHub stars into lists: see my stars.

Contact: sylvain.combettes8 [a t] gmail.com

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  1. probabl-ai/skore probabl-ai/skore Public

    The scikit-learn Modeling Companion

    Python 128 9

  2. astride astride Public

    [EUSIPCO 2024] Python implementation of "ASTRIDE: Adaptive Symbolization for Time Series Databases"

    Jupyter Notebook 16 3

  3. d-symb d-symb Public

    [ICDMW 2023] Python implementation of d_{symb}: "An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals"

    Jupyter Notebook 9

  4. boniolp/dsymb-playground boniolp/dsymb-playground Public

    [ICDE 2024] Python and Streamlit implementation of "d_{symb} playground: an interactive tool to explore large multivariate time series datasets"

    Python 13 2

  5. medgan-tips medgan-tips Public

    [Python] Additional works on Edward Choi's medGAN (generative adversarial network for electronic health records). In particular: boosting the prediction score using dataset augmentation.

    Jupyter Notebook 23 4

  6. comparison-distributions comparison-distributions Public

    [Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. Kullback-Leibler). Application to the Choquet integral.

    Jupyter Notebook 11