Parameterized Explainer for Graph Neural Network

Overview

PGExplainer

This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network

https://arxiv.org/abs/2011.04573

NeurIPS 2020

Requirements

  • Python 3.6.8
  • tensorflow 2.0
  • networkx

References

@article{luo2020parameterized,
  title={Parameterized Explainer for Graph Neural Network},
  author={Luo, Dongsheng and Cheng, Wei and Xu, Dongkuan and Yu, Wenchao and Zong, Bo and Chen, Haifeng and Zhang, Xiang},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  year={2020}
}

Pytorch Implementation

Here are several re-implementations and reproduction reports from other groups. Thanks very much these researchers for re-implementing PGExplainer to make it more easy to use!

  1. [Re] Parameterized Explainer for Graph Neural Network

https://zenodo.org/record/4834242/files/article.pdf

Code:

https://github.com/LarsHoldijk/RE-ParameterizedExplainerForGraphNeuralNetworks

Note that in this report, they adopt different GCN models with our implementation.

  1. Reproducing: Parameterized Explainer for Graph NeuralNetwork

https://openreview.net/forum?id=tt04glo-VrT

Code:

https://openreview.net/attachment?id=tt04glo-VrT&name=supplementary_material

  1. DIG

https://github.com/divelab/DIG/tree/main/dig/xgraph/PGExplainer

Owner
Dongsheng Luo
Ph.D. Student @ PSU
Dongsheng Luo
[3DV 2021] A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks

dispersion-score Official implementation of 3DV 2021 Paper A Dataset-dispersion Perspective on Reconstruction versus Recognition in Single-view 3D Rec

Yefan 7 May 28, 2022
Pytorch implementation of Decoupled Spatial-Temporal Transformer for Video Inpainting

Decoupled Spatial-Temporal Transformer for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, J

51 Dec 13, 2022
CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary.

CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre

1 Oct 27, 2021
Code for the paper Hybrid Spectrogram and Waveform Source Separation

Demucs Music Source Separation This is the 3rd release of Demucs (v3), featuring hybrid source separation. For the waveform only Demucs (v2): Go this

Meta Research 4.8k Jan 04, 2023
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha

Winnie Xu 95 Nov 26, 2021
efficient neural audio synthesis in the waveform domain

neural waveshaping synthesis real-time neural audio synthesis in the waveform domain paper • website • colab • audio by Ben Hayes, Charalampos Saitis,

Ben Hayes 169 Dec 23, 2022
EigenGAN Tensorflow, EigenGAN: Layer-Wise Eigen-Learning for GANs

Gender Bangs Body Side Pose (Yaw) Lighting Smile Face Shape Lipstick Color Painting Style Pose (Yaw) Pose (Pitch) Zoom & Rotate Flush & Eye Color Mout

Zhenliang He 321 Dec 01, 2022
PyTorch implementation of MLP-Mixer

PyTorch implementation of MLP-Mixer MLP-Mixer: an all-MLP architecture composed of alternate token-mixing and channel-mixing operations. The token-mix

Duo Li 33 Nov 27, 2022
Code to generate datasets used in "How Useful is Self-Supervised Pretraining for Visual Tasks?"

Synthetic dataset rendering Framework for producing the synthetic datasets used in: How Useful is Self-Supervised Pretraining for Visual Tasks? Alejan

Princeton Vision & Learning Lab 21 Apr 29, 2022
Pure python implementations of popular ML algorithms.

Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks

Alexis Gidiotis 3 Jan 10, 2022
Transformer part of 12th place solution in Riiid! Answer Correctness Prediction

kaggle_riiid Transformer part of 12th place solution in Riiid! Answer Correctness Prediction. Please see here for more information. Execution You need

Sakami Kosuke 2 Apr 23, 2022
Label Mask for Multi-label Classification

LM-MLC 一种基于完型填空的多标签分类算法 1 前言 本文主要介绍本人在全球人工智能技术创新大赛【赛道一】设计的一种基于完型填空(模板)的多标签分类算法:LM-MLC,该算法拟合能力很强能感知标签关联性,在多个数据集上测试表明该算法与主流算法无显著性差异,在该比赛数据集上的dev效果很好,但是由

52 Nov 20, 2022
Towards End-to-end Video-based Eye Tracking

Towards End-to-end Video-based Eye Tracking The code accompanying our ECCV 2020 publication and dataset, EVE. Authors: Seonwook Park, Emre Aksan, Xuco

Seonwook Park 76 Dec 12, 2022
Official Pytorch Code for the paper TransWeather

TransWeather Official Code for the paper TransWeather, Arxiv Tech Report 2021 Paper | Website About this repo: This repo hosts the implentation code,

Jeya Maria Jose 81 Dec 30, 2022
deep_image_prior_extension

Code for "Is Deep Image Prior in Need of a Good Education?" Project page: https://jleuschn.github.io/docs.educated_deep_image_prior/. Supplementary Ma

riccardo barbano 7 Jan 09, 2022
Tutorial to set up TensorFlow Object Detection API on the Raspberry Pi

A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi

Evan 1.1k Dec 26, 2022
PCGNN - Procedural Content Generation with NEAT and Novelty

PCGNN - Procedural Content Generation with NEAT and Novelty Generation Approach — Metrics — Paper — Poster — Examples PCGNN - Procedural Content Gener

Michael Beukman 8 Dec 10, 2022
EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation

EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The

16 Dec 07, 2022
hipCaffe: the HIP port of Caffe

Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Cent

ROCm Software Platform 126 Dec 05, 2022
a grammar based feedback fuzzer

Nautilus NOTE: THIS IS AN OUTDATE REPOSITORY, THE CURRENT RELEASE IS AVAILABLE HERE. THIS REPO ONLY SERVES AS A REFERENCE FOR THE PAPER Nautilus is a

Chair for Sys­tems Se­cu­ri­ty 158 Dec 28, 2022