Self-supervised learning on Graph Representation Learning (node-level task)

Last update: Dec 31, 2021

Related tags

Deep Learning graph_SSL

Overview

graph_SSL

Self-supervised learning on Graph Representation Learning (node-level task)

How to run the code

To run GRACE, sh run_GRACE.sh
To run GCA, sh run_GCA.sh
To run BGRL, sh run_BGRL.sh

Experimental Results

You can check detailed experimental results in results folder.

name	WikiCS	Amazon Computers	Amazon Photo	Coauthor CS	Coauthor Physics
`GRACE`	78.41	86.44	90.02	92.63	OOM
`GCA`	78.42	88.06	89.85	92.77	OOM
`BGRL`	79.50	88.338	92.83	92.49	94.89

Implemented

Implemented paper list

name	Paper
`GRACE`	paper
`GCA`	paper
`BGRL`	paper

Codes borrowed from

name	Implementation Code	Paper
`GRACE`	Implementation	paper
`GCA`	Implementation	paper
`Bootstrap Your Own Latent`	Implementation	paper
`SelfGNN`	Implementation	paper

Owner

Namkyeong Lee

GitHub Repository

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Self-supervised learning on Graph Representation Learning (node-level task)

Related tags

Overview

graph_SSL

How to run the code

Experimental Results

Implemented

Codes borrowed from

Owner

Namkyeong Lee

Self Governing Neural Networks (SGNN): the Projection Layer

2D Time independent Schrodinger equation solver for arbitrary shape of well

[cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

From a body shape, infer the anatomic skeleton.

Package to compute Mauve, a similarity score between neural text and human text. Install with `pip install mauve-text`.

Image segmentation with private İstanbul Dataset

PointPillars inference with TensorRT

Experiments for distributed optimization algorithms

Code release for NeRF (Neural Radiance Fields)

The object detection pipeline is based on Ultralytics YOLOv5

"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022)

Official PyTorch implemention of our paper "Learning to Rectify for Robust Learning with Noisy Labels".

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Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.

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