Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Last update: Oct 28, 2022

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Overview

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Setup

This implementation is based on PyTorch >= 1.0.0. Small dataset (including Cora, Citeseer, and Pubmed) are located in the data folder.

Usage

Please use the jupyter notebook files localed in the ./jupyter_notebooks. Please copy the file you want to run to the root folder, i.e., ./DGCN/CODE_WANT_TO_RUN.ipynb, then directly run it using jupyter notebook.

Owner

Weilin Cong

Graduate student at Pennsylvania State University.

GitHub Repository

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Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Related tags

Overview

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Setup

Usage

Owner

Weilin Cong

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