gcastle_notears_nonlinear

NO TEARS non-linear

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

Description

Example JSON

[
  {
    "id": "gcastle_notears_mlp",
    "lambda1": 0.01,
    "lambda2": 0.01,
    "max_iter": 100,
    "h_tol": "1e-8",
    "rho_max": "1e+16",
    "w_threshold": 0.3,
    "bias": true,
    "model_type": "mlp",
    "device_type": "cpu",
    "device_ids": null,
    "timeout": null
  },
  {
    "id": "gcastle_notears_sob",
    "lambda1": 0.01,
    "lambda2": 0.01,
    "max_iter": 100,
    "h_tol": "1e-8",
    "rho_max": "1e+16",
    "w_threshold": 0.3,
    "bias": true,
    "model_type": "sob",
    "device_type": "cpu",
    "device_ids": null,
    "timeout": null
  }
]

[1]

Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, and Eric Xing. Learning sparse nonparametric dags. In Silvia Chiappa and Roberto Calandra, editors, Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, volume 108 of Proceedings of Machine Learning Research, 3414–3425. PMLR, 26–28 Aug 2020. URL: https://proceedings.mlr.press/v108/zheng20a.html.