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final-project-10708's Introduction

CMU 10708 Final Project

Introduction

We propose an no-acyclic constrain learning paradigm for DAG discovery. We also benchmark established algorithms on synthetic data.

Requirements

please install

Synthetic Data

The constructed synthetic data on 10, 20, 50, 100 nodes Erdos-Renyi graph are at:

$ project-708/data_p10_e10_n1000_GP
$ project-708/data_p20_e20_n1000_GP
$ project-708/data_p50_e50_n1000_GP
$ project-708/data_p100_e100_n1000_GP

To Test

NOTEARS

$ cd notears/
$ python notears/linear.py

AutoPerm (ours)

$ cd notears/
$ python notears/perm_linear.py

DAGMA

$ cd dagma/
$ python dagma/dagma_linear.py

GOLEM

$ cd golem/
$ python src/golem.py

DAG-GNN

$ cd DAG-GNN/
$ python src/train.py

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