gcastle_notears_low_rank

NO TEARS low rank

Package	gCastle
Version	1.0.3
Language	Python
Docs
Paper	Fang et al.[1]
Graph type	DAG
Docker	bpimages/gcastle:1.0.3
Module folder	gcastle_notears_low_rank

Description

Adapting NOTEARS for large problems with low-rank causal graphs.

Example JSON

[
  {
    "id": "gcastle_notears_low_rank",
    "rank": 15,
    "w_init": null,
    "max_iter": 15,
    "h_tol": "1e-6",
    "rho_max": "1e+20",
    "w_threshold": 0.3,
    "timeout": null
  }
]

[1]

Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, and Yangbo He. Low rank directed acyclic graphs and causal structure learning. 2020. URL: https://arxiv.org/abs/2006.05691.