Source code of manuscript: Kim. D. 2025. "Hand Drawing Image based Causal Representation Learning for Robust Parkinson’s Disease Feature Extraction and Detection". BioRxiv. pp. 1-11. https://doi.org/10.1101/2025.06.01.657220

LungCRCT source code

Source code of LightHCG model. D, Kim(2025), "LightHCG: a Lightweight yet powerful HSIC Disentanglement based Causal Glaucoma Detection Model framework", arXiv:2512.02437, pp. 1-11.

This is a source code of manuscript: Kim D. 2024. "Graph Autoencoder and StrNN based Causal Analysis of Mortality in Heart Failure Patients". BioRxiv. DOI: https://doi.org/10.1101/2024.11.11.622921

This is a github soure code repository for manuscript: Kim D. 2025. "CVAE-based Causal Representation Learning from Retinal Fundus Images for Age Related Macular Degeneration(AMD) Prediction". BioRxiv. DOI: https://doi.org/10.1101/2025.02.13.638092

Code for the paper “Discrete 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.

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

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

mirror of the MeDIL Python package for causal modeling

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

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

Code Repository for ICM-VAE (IJCAI 2024)

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

Code Repository for SCM-VAE (IEEE Big Data)

A Survey on Causal Generative Modeling (TMLR 2024)

Multi-Instance Causal Representation Learning

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

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

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