jneuer / pearl-primerLinks
Notes for Judea Pearl et al., *Causal Inference in Statistics, a Primer*
☆68Updated 6 years ago
Alternatives and similar repositories for pearl-primer
Users that are interested in pearl-primer are comparing it to the libraries listed below
Sorting:
- A curated list of awesome work on causal inference, particularly in machine learning.☆108Updated 4 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Resources related to causality☆267Updated last year
- Example causal datasets with consistent formatting and ground truth☆90Updated 5 months ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆340Updated 11 months ago
- A (concise) curated list of awesome Causal Inference resources.☆243Updated 3 years ago
- ☆190Updated 2 years ago
- Solutions on "Causal Inference in Statistics: A Primer" using Jupyter Notebook, Python☆31Updated 7 years ago
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆72Updated this week
- ☆36Updated 3 months ago
- A data index for learning causality.☆477Updated last year
- Notebooks for Applied Causal Inference Powered by ML and AI☆133Updated 6 months ago
- Materials Collection for Causal Inference☆47Updated 2 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- CSuite: A Suite of Benchmark Datasets for Causality☆76Updated 2 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Active Bayesian Causal Inference (Neurips'22)☆58Updated last year
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 9 months ago
- Causal Inference in Python☆44Updated last week
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆158Updated 4 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 5 months ago
- Short tutorials on the use of machine learning methods for causal inference☆48Updated 2 years ago
- Project on Causal Machine learning CS 7290☆16Updated 5 years ago
- Causal discovery algorithms and tools for implementing new ones☆228Updated 2 months ago
- ☆10Updated 3 years ago
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆60Updated 5 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆154Updated 2 years ago
- Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"☆161Updated last year
- Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)☆31Updated last year