Repository Index

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

• causal-inference
• machine-learning
• graphical-models
• bayesian-networks

Uplift modeling and causal inference with machine learning algorithms

• incubation
• machine-learning
• causal-inference
• uplift-modeling

Visual Causal Flow

Python Toolkit for Causal and Probabilistic Reasoning

• python
• bayesian-networks
• causal-inference
• causal-discovery

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

• calibration
• causal-inference
• cold-start
• contrastive-learning

[RSS 2026] Causal video-action world model for generalist robot control

Causal Discovery in Python. Learning causality from data.

• causal
• causal-discovery
• causal-inference
• causality

Corpus legislativo brasileiro em larga escala e modelo Transformer causal treinado do zero em PyTorch puro.

Open standard for Provenance & Intent Contracts (PIC) in AI agents. Verify intent, provenance, and evidence before high-impact tool calls.

• action-proposals
• agentic-ai
• agents
• ai