34 Open source projects that are alternatives of or similar to cobalt

Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Implement PC algorithm in Python | PC 算法的 Python 实现

ParamHelpers Next Generation

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

DoubleML - Double Machine Learning in R

💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.

DoubleML - Double Machine Learning in Python

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

Causal Inference: What If. R and Stata code for Exercises

🎓 GSU MPA/MPP course on program evaluation and causal inference

Nonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests

Algorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.

A minimalist framework for rapid server side applications prototyping in C++ with dependency injection support.

A Python package for causal inference using Synthetic Controls

Policy learning via doubly robust empirical welfare maximization over trees

This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.

Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)

Must-read papers and resources related to causal inference and machine (deep) learning

Machine learning based causal inference/uplift in Python

Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure

➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.

CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data

[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

🎯 📕 Targeted Learning in R: A Causal Data Science Handbook

My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context

Coz: Causal Profiling

Uplift modeling and causal inference with machine learning algorithms

Python Library for learning (Structure and Parameter) and inference (Probabilistic and Causal) in Bayesian Networks.

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.

Python package for the creation, manipulation, and learning of Causal DAGs

Olympus: a benchmarking framework for noisy optimization and experiment planning