bradendubois / do-calculusLinks
A Python implementation of the do-calculus of Judea Pearl et al.
☆28Updated this week
Alternatives and similar repositories for do-calculus
Users that are interested in do-calculus are comparing it to the libraries listed below
Sorting:
- python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.☆25Updated 2 years ago
- Machine learning based causal inference/uplift in Python☆61Updated last year
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 8 months ago
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 4 years ago
- A system for Bayesian estimation of state space models using PyMC☆35Updated last month
- State Space Estimation of Time Series Models in Python: Statsmodels☆44Updated 8 years ago
- Causing: CAUsal INterpretation using Graphs☆58Updated 2 weeks ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 4 months ago
- ☆14Updated last year
- Unstructured Code with interesting analysis☆37Updated 10 months ago
- Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)☆13Updated 2 months ago
- Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks (currently Python & R)☆20Updated this week
- A python package for hierarchical forecasting, inspired by hts package in R.☆28Updated 6 months ago
- In which I play with the ideas surrounding causality☆53Updated 3 years ago
- Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference☆53Updated this week
- Machine Learning models using a Bayesian approach and often PyMC3☆25Updated 4 years ago
- Causal Inference Using Quasi-Experimental Methods☆20Updated 4 years ago
- Fit Sparse Synthetic Control Models in Python☆85Updated last year
- ☆78Updated 5 years ago
- A resource list for causality in statistics, data science and physics☆265Updated last month
- Bayesian Bandits☆68Updated 2 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated last month
- Comparing different performance estimation methods for time series forecasting tasks☆37Updated 4 months ago
- A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.☆56Updated last year
- Causal Inference in Python☆44Updated 7 months ago
- Notebooks for Applied Causal Inference Powered by ML and AI☆128Updated 5 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".☆24Updated last year
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- Code for blog posts.☆20Updated last year