This repository is a collection of trustworthy AI related works from Huawei Noah's Ark Lab.

• A causal structure learning toolchain containing various functionalities related to causal learning and evaluation. A tech report describing the toolbox is available here.
• The package offers a number of causal discovery algorithms, most of which are gradient-based, hence the name: gradient-based Causal structure learning pipeline.

• Information and baselines for causality-related competitions arranged by Noah's Ark Lab.
• Previous competitions were held at PCIC 2021, PCIC 2022, and NeurIPS 2023.

• Real-world datasets released by Huawei Noah's Ark Lab.
• Code for generating various synthetic datasets.

• Research works related to causality. We will continuously add new methods here.
• Currently contains implementations of CausalVAE, GAE, and causal discovery with reinforcement learning.