DIRECT

IJCAI 2021 Paper: Multi-Cause Effect Estimation with Disentangled Confounder Representation

Environment

• python 3.6.5
• numpy 1.18.3
• pytorch 1.6.0
• nltk 3.2.2

Data simulation

$ python data_synthetic.py

ITE estimation

$ python main_disent.py --dataset synthetic --K 4 --dim_zt 32 --dim_zi 32 --lr 1e-3 --beta 20 --epochs 251 

Reference

[1] Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li, “Multi-Cause Effect Estimation with Disentangled Confounder Representation”, International Joint Conference on Artificial Intelligence (IJCAI), 2021.