DMIRLAB-Group / SELFLinks
Provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI,2018."
☆16Updated 8 years ago
Alternatives and similar repositories for SELF
Users that are interested in SELF are comparing it to the libraries listed below
Sorting:
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- 把因果思维融入机器学习中☆81Updated 6 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆77Updated 4 years ago
- ☆205Updated 2 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆161Updated 4 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆131Updated 2 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆64Updated 5 years ago
- ☆59Updated 3 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆93Updated 2 years ago
- This code provide the CANM algorithim for causal discovery. Please cite "Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. Cau…☆16Updated 6 years ago
- ☆287Updated 3 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆66Updated 5 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
- Source code of The Neural Hawkes Process (NIPS 2017)☆228Updated 4 years ago
- Causal Effect Inference with Deep Latent-Variable Models☆354Updated 5 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆50Updated 6 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…☆21Updated 4 years ago
- Counterfactual Regression☆317Updated 3 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆153Updated last year
- A curated list of awesome work on causal inference, particularly in machine learning.☆112Updated 4 years ago
- ☆36Updated 3 months ago
- ☆317Updated 4 years ago
- Datasets for Causal-Structure-Learning Repo☆15Updated 5 years ago
- A data index for learning causality.☆480Updated 2 years ago
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆92Updated 3 years ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- A generalized score-based method for Causal Discovery☆19Updated 5 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆67Updated last year
- CPDAG Estimation using PC-Algorithm☆95Updated 3 years ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆340Updated last year