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Trustworthy AI

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


The NeurIPS 2023 Causal Structure Learning Competition has released, looking forward to your participation!

NeurIPS 2023|CSL Competition


gCastle

  • 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.

Competition

  • Information and baselines for causality-related competitions arranged by Noah's Ark Lab.

Datasets

  • Code for generating synthetic datasets and real-world datasets that we have open-sourced.

Research

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

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  • Python 95.1%
  • Jupyter Notebook 4.8%
  • HTML 0.1%