paras2612 / CauseBoxLinks
Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensignificant advances through the application of machine learningtechniques, especially deep neural networks. Unfortunately, to-datemany of the proposed methods are evaluated on different (data,software/hardware, h…
☆21Updated 3 years ago
Alternatives and similar repositories for CauseBox
Users that are interested in CauseBox are comparing it to the libraries listed below
Sorting:
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 3 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
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- ☆33Updated 2 years ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆17Updated 2 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 2 years ago
- ☆39Updated 6 years ago
- ☆45Updated 6 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 7 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆35Updated 2 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆61Updated 5 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 3 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆128Updated 2 years ago
- ☆92Updated 2 years ago
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…☆30Updated 4 years ago
- ☆27Updated 2 years ago
- ☆58Updated 3 years ago
- pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆69Updated 4 years ago
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆22Updated last year
- ☆44Updated last year
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆140Updated 11 months ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning☆41Updated 3 months ago
- Code for Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021)☆12Updated 3 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆88Updated 2 years ago
- ☆19Updated this week
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆30Updated 5 years ago
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 3 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆75Updated 4 years ago