Vincent Jeanselme's Projects
Markdown source for Michael Abrash's Graphics Programming Black Book
Test the adaBoost algorithm on multiple neural networks.
Exploration of a Kaggle competition step by step
Python script to export Apple Health dump file to a data frame for analysis.
Primitives for the D3M program
Implementation of "Identifying treatment response subgroups in observational time-to-event data" Jeanselme et al.
Generates random points with label in order to test neural networks and visualize there results.
Clustering for labeled data
Code to reproduce results from "Fairness under Clinical Presence: Impact of missingness mechanisms on sub-populations performance"
A little library in order to compute linear regression between several colors.
COVID 19 - Simple regression
D Calibration for survival data
Deep Survival Machines - Fully Parametric Survival Regression
Transform an input image thanks to Delaunay triangulation
Repository for the overview paper "Deep Learning for Survival Analysis: A Survey"
Tools and simple tests on quick-draw dataset
Dynamic Deep Hit - Pytorch implementation
Comparison of gradient descent algorithms
Analysis of the absent data in order to select the subset of features shared by the most patients
Food Publications and Datasets
Implementation of the algorithm of growcut in c++ with an interface in python
Analysis of the MNIST database : http://yann.lecun.com/exdb/mnist/
Hough Transform Computation
Compress an image thanks to matrix factorisation.
:exclamation: This is a read-only mirror of the CRAN R package repository. ipw — Estimate Inverse Probability Weights
Front page
Updated website
Competition of classification
Simple implementation of a kernel ckmeans