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innsight

Interpretability methods to analyze the behavior and individual predictions of modern neural networks in R.

interplot

interplot: plotting interactive effects

introductioncausaldiscovery

jmlr_20-175_supplement

Code for the simulation studies in "On Efficient Adjustment in Causal Graphs" by Witte, Henckel, Maathuis, Didelez (2020), Journal of Machine Learning Research

jss_innsight

methods_week

ZeSOB Methods Weeks in Statistics on Interpretable Machine Learning

micd

Multiple Imputation in Causal Graph Discovery

networks

Different Network Packages

neuralnet

Training of Neural Networks

practicalguide

pvm

A collection of signal detection methods used in the field of pharmacovigilance

pvmcomparison

R package for comparing various methods used in the field of pharmacovigilance to detect associations between drugs and adverse events in spontaneous reporting data

rgp

Identification of Risk Groups in Pharmacovigilance Using Penalized Regression (RGP)

sdgym

Benchmarking synthetic data generation methods.

semisynthetic_data_simulation

Comparing various variable selection methods on semisynthetic TCGA data

simplerf_maxstat

simsham

simtracker

An R package designed for tracking and management of simulation studies for both the BIPS workstation and local machines

srsim

An R package for simulating spontaneous reports

statmed_missingcausaldiscovery

survnet

Artificial neural networks for survival analysis

synthcity

A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.

toward_understanding_disagreement_problem

tpc

tPC - Causal discovery with temporal background

unfooling_shapley

wflsa

Weighted Fused Lasso Signal Approximator (wFLSA)