csetraynor

causal_salad_2021

One day course on causal inference, MPI-EVA 9 September 2021

clairvoyance

Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series

ctsem

Hierarchical continuous time state space modelling

deep-learning-building-blocks

Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

drc

Fitting dose-response models in R

free_r_tips

Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every Tuesday.

gfoRmula

Parametric G-formula for R

ggPMX

ggPMX R package

GPWeibull

Gaussian Process for varying treatment effects with the Weibull distribution

JMbayes2

Extended Joint Models for Longitudinal and Survival Data

mcstate

:sparkles::broom: Monte-Carlo State Space Models

mice

Multivariate Imputation by Chained Equations

miml-synthetic

Code for "Imputing biomarker status from RWE data sets-a comparative study"

NMproject

Turning R and RStudio into a NONMEM model development environment

ompi

Open MPI main development repository

otsbounds

OTS Bounds for causal survival analyses

PopED

Population Experimental Design (PopED) in R

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.

pywick

High-level batteries-included neural network training library for Pytorch

rcgan-pytorch

This is a PyTorch implementation of Recurrent (Conditional) GAN (Esteban et al., 2017)

tabnet

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

tabnet-1

An R implementation of TabNet

tabnet-modified

Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"

targets

Function-oriented Make-like declarative workflows for R

TimeGAN

Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019

timegan-pytorch

This repository holds the code for the reimplementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch

tips

Most commonly used git tips and tricks.

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow