Stars
Source code to reproduce results from "Exploring Drivers of Gene Expression in The Cancer Genome Atlas" by Rau et al. (2017)
An algorithm to solve SLOPE optimization problem and compute its solution path.
Confidence and prediction intervals for nonlinear regression in Python, Jupyter Notebook, and MATLAB using the delta-method or parametric bootstrap
Make sankey, alluvial and sankey bump plots in ggplot
R package sharp (Stability-enHanced Approaches using Resampling Procedures).
Blazing fast inference of PLN models built on top of Python and PyTorch
A beautiful, simple, clean, and responsive Jekyll theme for academics
pytorch tutorial for beginners
Macrolitter video counting on riverbanks using state space models and moving cameras
A header-only C++ library for numerical optimization --
Rcpp integration for the Ensmallen templated C++ mathematical optimization library
nloptr provides an R interface to NLopt, a free/open-source library for nonlinear optimization providing a common interface to a number of different optimization routines which can handle nonlinear…
library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization
Unofficial collection of templates and themes in line with INRAE's design system
"Trade-of between deep learning for species identication...", by Olivier Gimenez et al
Tutorials and experiments related to deep learning
PyTorch Tutorial for Deep Learning Researchers
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris
Open-source scientific and technical publishing system built on Pandoc.
Computo template and documentation for R users
GREED: R package for Bayesian greedy clustering with several discrete latent variable models #sbm, #dcsbm, #dclbm #mm, #gmm
This is the development site for Hands-On Programming with R, a book that teaches how to program in R, with hands-on examples. Read the book at https://rstudio-education.github.io/hopr.
Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
Annexes R Approche Statistiques pour les variables cachées en écologie coordonné par N. Peyrard et O. Gimenez