causal-representation-learning

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

Large Causal Models for Temporal Causal Discovery [ECML PKDD '26]

mirror of the MeDIL Python package for causal modeling

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

Official implementation of "Modeling Soft Intervention Effects for Implicit Causal Representation Learning" (Machine Learning, Springer 2026). ICRL-SM learns identifiable causal representations from soft interventions via a causal mechanism switch variable.

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.