917 Open source projects that are alternatives of or similar to Dowhy

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

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

Machine learning based causal inference/uplift in Python

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

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

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.

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

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。

Software for learning sparse Bayesian networks

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

Library for graphical models of decision making, based on pgmpy and networkx

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

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

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

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

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

C++ based implementation of StatNLP framework

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

A Python package for causal inference using Synthetic Controls

QM model-based design tool and code generator based on UML state machines

Methods for subgroup identification / personalized medicine / individualized treatment rules

Java-based server framework of the graphical language server platform

Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"

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

Markov random fields with covariates

Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893

Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution Prediction" (NeurIPS-21)

Implement PC algorithm in Python | PC 算法的 Python 实现

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

CAusal Reasoning for Network Identification with integer VALue programming in R

Covariate Balance Tables and Plots - An R package for assessing covariate balance

💉📈 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.

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

Automatic probabilistic programming for scientific machine learning and dynamical models

Causal Deconvolution of Networks by Algorithmic Generative Models

Policy learning via doubly robust empirical welfare maximization over trees

A Code-First Introduction to NLP course

pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models

Regulatory networks with Direct Information in python

DoubleML - Double Machine Learning in R

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

Distributed scikit-learn meta-estimators in PySpark

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

DoubleML - Double Machine Learning in Python

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

Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering | Python3 | PyTorch | CNNs | Causality | Reasoning | LSTMs | Transformers | Multi-Head Self Attention | Published in IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

Example diagram editors built with Eclipse GLSP

Causing: CAUsal INterpretation using Graphs

Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.

🎲 A Kotlin DSL for probabilistic programming.

Linear Gaussian Bayesian Networks - Inference, Parameter Learning and Representation. 🖧

Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum

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

Code for our paper, Neural Network Attributions: A Causal Perspective (ICML 2019).

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

An implementation of Bayesian Networks Model for pure C++14 (11) later, including probability inference and structure learning method.

Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

An Open Source, Self-Hosted Platform For Applied Deep Learning Development