causal-machine-learning / kdd2021-tutorialLinks
EconML/CausalML KDD 2021 Tutorial
☆163Updated 2 years ago
Alternatives and similar repositories for kdd2021-tutorial
Users that are interested in kdd2021-tutorial are comparing it to the libraries listed below
Sorting:
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆67Updated last year
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆71Updated 5 months ago
- ☆105Updated 4 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆148Updated last year
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆341Updated last year
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆69Updated 5 years ago
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆108Updated 4 years ago
- ☆285Updated 3 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
- 💊 Comparing causality methods in a fair and just way.☆140Updated 5 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆91Updated 2 years ago
- A Python package for causal inference using Synthetic Controls☆192Updated last year
- Materials Collection for Causal Inference☆47Updated 2 years ago
- CausalLift: Python package for causality-based Uplift Modeling in real-world business☆349Updated 2 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆158Updated 4 years ago
- A (concise) curated list of awesome Causal Inference resources.☆243Updated 3 years ago
- A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.☆22Updated 8 years ago
- A data index for learning causality.☆478Updated 2 years ago
- Code and notebooks for my Medium blog posts☆129Updated last year
- pytorch implementation of dragonnet☆45Updated 3 years ago
- Resources related to causality☆266Updated last year
- AutoML for causal inference.☆231Updated 10 months ago
- Fixedeffectmodel: panel data modeling in Python☆79Updated 3 years ago
- ☆289Updated 2 years ago
- Repository with code and slides for a tutorial on causal inference.☆583Updated 6 years ago
- Must-read papers and resources related to causal inference and machine (deep) learning☆739Updated 2 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆62Updated 4 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 6 months ago
- Causal Inference in Python☆573Updated 4 months ago