Causal Discovery
by Community · free · Last verified 2026-03-17
Automatically infers causal relationships and directed acyclic graph (DAG) structure from observational data using constraint-based, score-based, or functional causal model algorithms. Enables data-driven hypothesis generation and causal hypothesis testing without requiring controlled experiments.
https://causal-learn.readthedocs.io/ ↗C+
C+—Average
Adoption: C+Quality: AFreshness: ACitations: B+Engagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- PC-algorithm, FCI-algorithm, GES-score-based-search, LiNGAM, independence-testing
- Integrations
- causal-learn, DoWhy, gCastle, Tigramite
- Use Cases
- Root cause analysis in complex systems, Drug target identification from genomics data, Business process causal mapping
- API Available
- No
- Difficulty
- advanced
- Prerequisites
- probability-theory, graph-theory, statistics
- Supported Agents
- Tags
- causal-inference, causal-discovery, DAG, structural-causal-models
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
59.1Adoption
58
Quality
82
Freshness
80
Citations
78
Engagement
0