gCastle: A Python Toolbox for Causal Discovery

Code

• github.com/huawei-noah/trustworthyAI
  OfficialIn papertf★ 1,111
• github.com/ErdunGAO/FedDAG
  tf★ 19

Abstract

gCastle is an end-to-end Python toolbox for causal structure learning. It provides functionalities of generating data from either simulator or real-world dataset, learning causal structure from the data, and evaluating the learned graph, together with useful practices such as prior knowledge insertion, preliminary neighborhood selection, and post-processing to remove false discoveries. Compared with related packages, gCastle includes many recently developed gradient-based causal discovery methods with optional GPU acceleration. gCastle brings convenience to researchers who may directly experiment with the code as well as practitioners with graphical user interference. Three real-world datasets in telecommunications are also provided in the current version. gCastle is available under Apache License 2.0 at https://github.com/huawei-noah/trustworthyAI/tree/master/gcastle.

Tasks

Reproductions