This repository is unofficial implementation of following papers with pytorch. The corresponding folder name is written in parenthesis.
- DAGs with NO TEARS: Continuous Optimization for Structure Learning (
notears) - DAG-GNN: DAG Structure Learning with Graph Neural Networks (
dag_gnn) - A Graph Autoencoder Approach to Causal Structure Learning (
gae) - Gradient-Based Neural DAG Learning (
gran_dag) - Learning Sparse Nonparametric DAGs (
notears_mlp) - Masked Gradient-Based Causal Structure Learning (
mcsl) - On the Role of Sparsity and DAG Constraints for Learning Linear DAGs (
golem) - DAGs with No Curl: An Efficient DAG Structure Learning Approach (
nocurl) - Penalized likelihood methods for estimation of sparse
high-dimensional directed acyclic graphs (
penalized)
- https://github.com/xunzheng/notears
- https://github.com/fishmoon1234/DAG-GNN
- https://github.com/huawei-noah/trustworthyAI/tree/master/Causal_Structure_Learning/GAE_Causal_Structure_Learning
- https://github.com/kurowasan/GraN-DAG
- https://github.com/huawei-noah/trustworthyAI/tree/master/gcastle/castle/algorithms/gradient/mcsl
- https://github.com/ignavierng/golem