Pinned Repositories
aeon
A toolkit for machine learning from time series
dsymb-playground
[ICDE 2024] Python and Streamlit implementation of "d_{symb} playground: an interactive tool to explore large multivariate time series datasets"
aeon
A unified framework for machine learning with time series
anomaly-detection-PCA
Anomaly detection on a production line using principal component analysis (PCA) and kernel principal component analysis (KPCA) *from scratch*.
astride
[Preprint] Python implementation of "ASTRIDE: Adaptive Symbolization for Time Series Databases"
C-for-data-science
C++ programming for Data Science. K-means clustering. K-nearest neighbor algorithm. Neural Networks.
comparison-distributions
[Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. Kullback-Leibler). Application to the Choquet integral.
d-symb
[ICDMW 2023] Python implementation of d_{symb}: "An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals"
high-dimensional-statistics
[Python, R] My homeworks for the Statistics for high-dimensional data course of my MSc @ Mines Nancy
medgan-tips
[Python] Additional works on Edward Choi's medGAN (generative adversarial network for electronic health records). In particular: boosting the prediction score using dataset augmentation.
sylvaincom's Repositories
sylvaincom/medgan-tips
[Python] Additional works on Edward Choi's medGAN (generative adversarial network for electronic health records). In particular: boosting the prediction score using dataset augmentation.
sylvaincom/astride
[Preprint] Python implementation of "ASTRIDE: Adaptive Symbolization for Time Series Databases"
sylvaincom/comparison-distributions
[Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. Kullback-Leibler). Application to the Choquet integral.
sylvaincom/anomaly-detection-PCA
Anomaly detection on a production line using principal component analysis (PCA) and kernel principal component analysis (KPCA) *from scratch*.
sylvaincom/d-symb
[ICDMW 2023] Python implementation of d_{symb}: "An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals"
sylvaincom/C-for-data-science
C++ programming for Data Science. K-means clustering. K-nearest neighbor algorithm. Neural Networks.
sylvaincom/aeon
A unified framework for machine learning with time series
sylvaincom/high-dimensional-statistics
[Python, R] My homeworks for the Statistics for high-dimensional data course of my MSc @ Mines Nancy
sylvaincom/sylvaincom
My personal repository.
sylvaincom/sylvaincom.github.io
My website
sylvaincom/non-tech
work in progress
sylvaincom/symb-rep
[EUSIPCO 2024] Python implementation of ASTRIDE: "Symbolic representation for time series"