napsternxg / awesome-causality
Resources related to causality
☆262Updated last year
Alternatives and similar repositories for awesome-causality
Users that are interested in awesome-causality are comparing it to the libraries listed below
Sorting:
- A data index for learning causality.☆467Updated last year
- A (concise) curated list of awesome Causal Inference resources.☆233Updated 2 years ago
- Repository with code and slides for a tutorial on causal inference.☆575Updated 5 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆103Updated 4 years ago
- Must-read papers and resources related to causal inference and machine (deep) learning☆710Updated 2 years ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆324Updated 7 months ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆762Updated 9 months ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 3 years ago
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.☆416Updated 4 years ago
- Non-parametrics for Causal Inference☆45Updated 3 years ago
- Causal Inference in Python☆568Updated 4 years ago
- 💊 Comparing causality methods in a fair and just way.☆138Updated 5 years ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆110Updated 4 years ago
- Causal Graphical Models in Python☆246Updated 2 years ago
- Packages of Example Data for The Effect☆139Updated 6 months ago
- AutoML for causal inference.☆221Updated 4 months ago
- ☆78Updated 4 years ago
- EconML/CausalML KDD 2021 Tutorial☆161Updated last year
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆59Updated 5 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated 3 weeks ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆137Updated 10 months ago
- ☆467Updated 11 months ago
- A collection of visual guides to help applied scientists learn causal inference.☆268Updated 2 years ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- List of python packages for causal inference☆17Updated 3 years ago
- ☆185Updated 2 years ago
- Causal Effect Inference with Deep Latent-Variable Models☆338Updated 4 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 6 years ago
- A Python package for modular causal inference analysis and model evaluations☆775Updated last month