d909b / drnet
💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.
☆86Updated last year
Alternatives and similar repositories for drnet:
Users that are interested in drnet are comparing it to the libraries listed below
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆58Updated 4 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆125Updated last year
- ☆58Updated 2 years ago
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆71Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆133Updated 7 months ago
- Counterfactual Regression☆298Updated 2 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆81Updated 6 years ago
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…☆28Updated 4 years ago
- ☆253Updated 2 years ago
- Counterfactual Regression☆23Updated 8 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 3 years ago
- ☆31Updated 2 years ago
- BITES: Balanced Individual Treatment Effect for Survival data☆18Updated last year
- ☆40Updated 5 years ago
- ☆37Updated 6 years ago
- Causal Effect Inference with Deep Latent-Variable Models☆329Updated 4 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated last year
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆58Updated 10 months ago
- A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.☆22Updated 8 years ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆66Updated 6 months ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆155Updated 3 years ago
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆20Updated last year
- Causal Inference☆10Updated 4 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆59Updated 4 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
- Implementation of Johansson, Fredrik D., Shalit, Uri, and Sontag, David. Learning representations for counterfactual inference - ICML, 20…☆12Updated 4 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆22Updated 2 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆98Updated 3 years 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