rguo12/awesome-causality-algorithms resource

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3279 stars · 473 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated awesome-list index of open-source algorithms and toolboxes for learning causality with data, covering causal inference and causal machine learning. It accompanies an ACM Computing Surveys paper and only lists methods with available code.

Use cases

• find python libraries for causal inference
• discover causal discovery algorithms with open-source code
• compare toolboxes for treatment effect estimation
• find uplift modeling packages
• research survey of causal machine learning methods
• locate baselines for causal effect estimation

When to choose

• you need an overview of the causality algorithm landscape
• you are picking a causal inference toolbox for a project
• you want reproducible, code-backed causal methods

When to avoid

• you need a working library rather than a list of links
• you need methods without open-source implementations

Facets

learning-resource · maturity active

machine-learning developer-tools machine-learning data-science awesome-lists python causality causal-inference causal-discovery awesome-list uplift-modeling treatment-effect algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="rguo12/awesome-causality-algorithms")