Robust Causal Discovery and Inference Framework

Develop an advanced causal discovery system capable of inferring complex causal relationships from observational data using multiple statistical and machine learning techniques. Implement algorithmic approaches including constraint-based methods, score-based causal structure learning, and hybrid techniques. Create a comprehensive framework supporting causal graph estimation, intervention analysis, and uncertainty quantification. Include visualization of causal structures and automated hypothesis testing mechanisms.