UNN - Official Repository for Causal Neural Network
September 26, 2025 · View on GitHub
Overview
This repository provides our latest research on Causal Neural Network.
| Algorithm | Summary | Paper | Code |
|---|---|---|---|
| CUTS | EM-Style joint causal graph learning and missing data imputation for irregular temporal data | ICLR 2023 Latest Version | Code |
| CUTS+ | Increasing scalability of neural causal discovery on high-dimensional irregular data. | AAAI-24 Supplements | Code |
| CausalTime Benchmark | A novel pipeline capable of generating realistic time-series along with a ground truth causal graph that is generalizable to different fields. Official Website. | ICLR 2024 | Code |
| REACT | A causal deep learning approach that combines neural networks with causal discovery to develop a reliable and generalizable model to predict a patient's risk of developing CSA-AKI within the next 48 hours. | The Lancet Digital Health | Code |
🏥 Causal deep learning for real-time detection of cardiac surgery-associated acute kidney injury: derivation and validation in seven time-series cohorts
The Lancet Digital Health | Code🧑💻
🍺 CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Official Website ｜ ICLR 2024 | Generation Code🧑💻 ｜ Dataset Download
🎄CUTS+: High-dimensional Causal Discovery from Irregular Time-series
🚩 CUTS: Neural Causal Discovery from Irregular Time-Series Data
ICLR 2023 | Latest Version | Code🧑💻
