Code Monkey home page Code Monkey logo

gcn-lpa's Introduction

GCN-LPA

This repository is the implementation of GCN-LPA (arXiv):

Unifying Graph Convolutional Neural Networks and Label Propagation
Hongwei Wang, Jure Leskovec
arXiv Preprint, 2020

GCN-LPA is an end-to-end model that unifies Graph Convolutional Neural Networks (GCN) and Label Propagation Algorithm (LPA) for adaptive semi-supervised node classification.

Files in the folder

  • data/
    • citeseer/
    • cora/
    • pubmed/
    • ms_academic_cs.npz (Coauthor-CS)
    • ms_academic_phy.npz (Coauthor-Phy)
  • src/: implementation of GCN-LPA.

Running the code

$ python main.py

Note: The default dataset is Citeseer. Hyper-parameter settings for other datasets are provided in main.py.

Required packages

The code has been tested running under Python 3.6.5, with the following packages installed (along with their dependencies):

  • tensorflow == 1.12.0
  • networkx == 2.1
  • numpy == 1.14.3
  • scipy == 1.1.0
  • sklearn == 0.19.1
  • matplotlib == 2.2.2

gcn-lpa's People

Contributors

hwwang55 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

gcn-lpa's Issues

Reset Labels for Labeled Nodes in LPA

Hi,

In "model.py" when building lpa as following code, the labeled nodes seem not to be reset in the loop. I am wondering if this is correct. thank you!
def _build_lpa(self):
label_mask = tf.expand_dims(self.label_mask, -1)
input_labels = label_mask * self.labels
label_list = [input_labels]

    for _ in range(self.args.lpa_iter):
        lp_layer = LPALayer(adj=self.normalized_adj)
        hidden = lp_layer(label_list[-1])
        label_list.append(hidden)
    self.predicted_label = label_list[-1]

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.