Showing 1-20 of 23 projects
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions.
Causal inference and uplift modeling library for machine learning applications.
A toolkit for automated causal inference and econometric analysis, combining machine learning and econometrics.
Coz is a causal profiler for C/C++ that helps developers optimize performance by identifying bottlenecks.
A light-hearted yet rigorous approach to learning about impact estimation and causality in Python.
An index of algorithms for learning causality with data, useful for vibe coders working on AI-powered applications.
Python library for Causal AI and Bayesian networks
Visual Causal Flow AI coding tool
A Python library to help data scientists infer causation from data rather than just observing correlation.
A comprehensive paper list and resource repository for Embodied AI research and development.
A real-time speech enhancement model that runs on a laptop CPU, useful for AI audio processing.
An R package for causal inference in time series analysis, useful for data-driven decision making.
Tigramite is a Python library for causal inference and time series analysis with a focus on time series data.
Causal Discovery in Python, including independence tests and score functions for causal inference.
Python code for causal inference, a book by Miguel Hernán and James Robins.
A repository with research notes on domain generalization, causality, robustness, and other ML topics.
A Python package for causal inference in graphs and pairwise settings, with tools for graph structure recovery and dependencies.
Eliot is a Python logging library that provides detailed causality analysis and tracing for complex distributed systems.
A Python package for causal inference in quasi-experimental settings
Open-source projects related to trustworthy AI, including causal discovery, causal inference, and causality.
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