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acceleep

Code for the master thesis re: Accelerometry-Based Prediction of Energy Expenditure […]

apts_causal_inference

Practicals for the APTS Module "Causal Inference"

arf

Adversarial Random Forests

arf_paper

Code and materials to reproduce adversarial RF paper

arfpy

Python implementation of adversarial random forests for density estimation and generative modelling

arm

Data Analysis Using Regression and Multilevel/Hierarchical Models

artpredict

Prediction with the ARTP

batchlasso

An R package for using the LASSO for ranking response-exposure pairs on the basis of the highest lambda for which they first appear in the active set

bips-hb.r-universe.dev

Index for the r-universe repository

bipsdown

RMarkdown templates with BIPS styles

blockforest

Random Forests for Blocks of Clinical and Omics Covariate Data

bscomparison

bsscomparison

Generates all the results from the paper "When choosing the best subset is not the best choice” by M. Hanke, L. Dijkstra, R. Foraita and V. Didelez

ccg-childhood-obesity

Analysis code

cfi_mixeddata

Code for paper "Conditional Variable Importance for Mixed Data" by Kristin Blesch, David S. Watson, Marvin N. Wright (2022)

countarfactuals

This repository contains the code for the countARFactuals paper.

cpi

CPI: Conditional Predictive Impact

cvn

Covariate-varying Networks

datatrain_workshop_ml

Workshop / hands-on component to the Data Train ML workshop

datatraincausallearning

Practicals for the Data Train Course "Causal learning" 2021 (V Didelez)

ee_prediction

expard

A simulator for EHC data and an algorithm to fit eight exposure models to data of this kind

expard-application

An application of the expard models on real-world data

expard-simulation-study

The simulation study for the exposure model paper

fitsham

generative_rf

Generative Random Forests

hccdsim

Simulator for Health Care Claims Data

idefics-score_calculator

Function in R to calculate percentiles, z-scores and Metabolic Syndrome (METS) scores for a given data set

iml_bremen_2023

Exercises for the Lecture in Interpretable Machine Learning taught at the University of Bremen in 2023

imlsa_2024

This repository contains code accompanying the paper "Interpretable Machine Learning for Survival Analysis"