Causal Discovery in Python. Learning causality from data.

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects"

Official code of the paper "BISCUIT: Causal Representation Learning from Binary Interactions" (UAI 2023)

[NeurIPS 2024] "Discovery of the Hidden World with Large Language Models"

Multi-Instance Causal Representation Learning

[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

A Survey on Causal Generative Modeling (TMLR 2024)

Code Repository for SCM-VAE (IEEE Big Data)

[NeurIPS 2024] Discovery of the Hidden World with Large Language Models

Code Repository for ICM-VAE (IJCAI 2024)

Análise do Impacto da Padronização de Markdown na Carga Cognitiva e Desempenho de Tarefas

These are listed papers from causal inference and causal representation learning in vision

mirror of the MeDIL Python package for causal modeling

Official Codebase for the paper "Large Causal Models for Temporal Causal Discovery", accepted at ECML PKDD 2026.

Code for paper "Causality Guided Representation Learning for Cross-Style Hate Speech Detection" (WWW2026)

[ICML 2026] Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

[BigDIA 2024] Deep Reinforcement Learning based Multi-UAV Collision Avoidance with Causal Representation Learning

This is a source code of manuscript: D, Kim(2025), "GCVAMD: A Modified CausalVAE Model for Causal Age-related Macular Degeneration Risk Factor Detection and Prediction", arXiv:2510.02781v1, pp. 1-11, 2025.

Non-linguistic models for structured ideation and causal world representations.