ignavierng / notears-tensorflowLinks
Reimplementation of NOTEARS in Tensorflow
☆33Updated 2 years ago
Alternatives and similar repositories for notears-tensorflow
Users that are interested in notears-tensorflow are comparing it to the libraries listed below
Sorting:
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆129Updated 2 years ago
- ☆95Updated 2 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
- CEVAE with VampPrior☆11Updated 7 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
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 4 years ago
- ☆40Updated 6 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated last year
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆90Updated 2 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆61Updated 4 years ago
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆71Updated this week
- Repository for "Differentiable Causal Discovery from Interventional Data"☆76Updated 3 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 4 years ago
- ☆18Updated 5 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
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆84Updated last year
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 3 years ago
- Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions☆11Updated 3 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆107Updated 4 years ago
- Causal Effect Inference with Deep Latent-Variable Models☆344Updated 5 years ago
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 4 years ago
- NeurIPS 2020 Spotlight Paper☆12Updated 3 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆65Updated 6 months ago