ghosthamlet / anankeLinks
Ananke named for the Greek primordial goddess of necessity and causality, is a python package for causal inference using the language of graphical models., import from https://gitlab.com/causal/ananke
☆15Updated 5 years ago
Alternatives and similar repositories for ananke
Users that are interested in ananke are comparing it to the libraries listed below
Sorting:
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆56Updated 7 months ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated last year
- Causal Graphical Models in Python☆250Updated 2 years ago
- A resource list for causality in statistics, data science and physics☆267Updated 2 months ago
- Tools for conformal inference in regression☆251Updated last year
- Fit Sparse Synthetic Control Models in Python☆87Updated last year
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆26Updated 3 weeks ago
- [Experimental] Global causal discovery algorithms☆110Updated 3 weeks ago
- Materials Collection for Causal Inference☆47Updated 2 years ago
- difference-in-differences in Python☆107Updated last year
- Basic time series modeling with Stan and Pystan☆33Updated 8 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆27Updated 4 years ago
- A unified interface for the estimation of causal networks☆22Updated 5 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 8 months ago
- Makes algorithms/code in Tetrad available in Python via JPype☆91Updated this week
- This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https…☆35Updated last year
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆27Updated 2 years ago
- ☆93Updated last year
- Example causal datasets with consistent formatting and ground truth☆102Updated 8 months ago
- Examples of PyMC models, including a library of Jupyter notebooks.☆359Updated last week
- Notebooks for Applied Causal Inference Powered by ML and AI☆143Updated 9 months ago
- ☆134Updated 2 weeks ago
- Code for Shopper, a probabilistic model of shopping baskets☆53Updated 5 years ago
- Bayesian Causal Forests☆52Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆153Updated last year
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆340Updated last year
- Python package to compute conditional and non-conditional causal effects.☆37Updated 3 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆161Updated 4 years ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆159Updated 2 weeks ago
- 💊 Comparing causality methods in a fair and just way.☆141Updated 5 years ago