amzn / credence-to-causal-estimation
A framework for generating complex and realistic datasets for use in evaluating causal inference methods.
☆30Updated 3 years ago
Alternatives and similar repositories for credence-to-causal-estimation:
Users that are interested in credence-to-causal-estimation are comparing it to the libraries listed below
- 💊 Comparing causality methods in a fair and just way.☆138Updated 4 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated last year
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆56Updated 9 months ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆82Updated 6 years ago
- ❓y0 (pronounced "why not?") is for causal inference in Python☆50Updated last week
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆152Updated last year
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆80Updated 2 months ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆71Updated 3 years ago
- Code for the paper "Temporally-Consistent Survival Analysis".☆25Updated 2 years ago
- ACM CHIL 2021: "Enabling Counterfactual Survival Analysis with Balanced Representations"☆12Updated 3 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆99Updated 5 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆56Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆58Updated 11 months ago
- ☆29Updated 6 years ago
- This course is an overview of applied causal inference.☆42Updated 5 months ago
- 🪜 Bayesian Hierarchical Models at Scale☆52Updated 3 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 7 months ago
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated last year
- Data Efficient Decision Making☆246Updated 2 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- ☆20Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆136Updated 8 months ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 3 years ago
- List of python packages for causal inference☆17Updated 3 years ago
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- ☆15Updated 7 months ago
- WIP predicted survival functions☆38Updated 5 years ago
- ☆87Updated 4 years ago