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

Python Toolkit for Causal and Probabilistic Reasoning

Coz: Causal Profiling

:arrow_lower_left: :arrow_lower_right: An R package for working with causal directed acyclic graphs (DAGs)

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

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.

A Python package for modular causal inference analysis and model evaluations

Python package for causal discovery based on LiNGAM.

A reproducibility lab for trading AI: published RL and LLM trading claims re-tested under a pre-registered protocol, with a causal benchmark and a live track.

Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.

Causal depthwise conv1d in CUDA, with a PyTorch interface

StatsPAI is the first agent-native Python platform for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, and R/Stata parity validation.

rCM & Causal-rCM: Leading and Unified Algorithms/Infrastructures for Bidirectional/Autoregressive Video Diffusion Distillation at Scale

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

[ICML 2026] Official codebase for "Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation" & Causal Forcing++

Local evidence debugger and trajectory-test toolkit for TypeScript AI agents: inspect causal runs, catch wrong tool paths in CI, and share safe offline evidence.

LLM agent 的有界自纠错长期记忆层：把连续、含矛盾的项目交互日志蒸馏成有界、可自更新的记忆库。Bounded, self-correcting long-term memory for LLM agents — candidate pool + value dynamics + tension adjudication + causal-replay evals.