Implementation for Simple Spectral Graph Convolution in ICLR 2021

Related tags

Deep LearningSSGC
Overview

Simple Spectral Graph Convolutional

Overview

This repo contains an example implementation of the Simple Spectral Graph Convolutional (S^2GC) model. This code is based on SGC. We will update the code in Text Classification and Node Clustering latter.

SGC removes the nonlinearities and collapes the weight matrices in Graph Convolutional Networks (GCNs) and is essentially a linear model. However, it also cannot beat GCNs in most benchmarks. S^2GC is a new baseline method for GCNs and downstream applications.

S^2GC achieves competitive performance while saving much training time, basically the computational cost is very close to SGC.

Dataset Metric
Cora Acc: 83.0 %
Citeseer Acc: 73.6 %
Pubmed Acc: 80.6 %
Reddit F1: 95.3 %

This home repo contains the implementation for citation networks (Cora, Citeseer, and Pubmed) and social network (Reddit).

Dependencies

Our implementation works with PyTorch>=1.0.0 Install other dependencies: $ pip install -r requirement.txt

Data

We provide the citation network datasets under data/, which corresponds to the public data splits.

Usage

$ python citation_cora.py
$ python citation_citeseer.py 
$ python citation_pubmed.py 
Owner
allenhaozhu
PhD Student
allenhaozhu
SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling

SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling Reference Main paper to be cited (Di Wu et al., 2020) @article

Moore 34 Nov 03, 2022
PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning

PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning

48 Dec 08, 2022
FACIAL: Synthesizing Dynamic Talking Face With Implicit Attribute Learning. ICCV, 2021.

FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning PyTorch implementation for the paper: FACIAL: Synthesizing Dynamic Talking

226 Jan 08, 2023
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

25 Dec 21, 2022
A repository for benchmarking neural vocoders by their quality and speed.

License The majority of VocBench is licensed under CC-BY-NC, however portions of the project are available under separate license terms: Wavenet, Para

Meta Research 177 Dec 12, 2022
A toy compiler that can convert Python scripts to pickle bytecode 🥒

Pickora 🐰 A small compiler that can convert Python scripts to pickle bytecode. Requirements Python 3.8+ No third-party modules are required. Usage us

ꌗᖘ꒒ꀤ꓄꒒ꀤꈤꍟ 68 Jan 04, 2023
Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

MI-AOD Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection (The PDF is not available tem

Tianning Yuan 269 Dec 21, 2022
Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021)

Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021) Tensorflow implementation of Bridging the Gap between Label- and Reference-ba

huangqiusheng 8 Jul 13, 2022
ShapeGlot: Learning Language for Shape Differentiation

ShapeGlot: Learning Language for Shape Differentiation Created by Panos Achlioptas, Judy Fan, Robert X.D. Hawkins, Noah D. Goodman, Leonidas J. Guibas

Panos 32 Dec 23, 2022
The code for the CVPR 2021 paper Neural Deformation Graphs, a novel approach for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects.

Neural Deformation Graphs Project Page | Paper | Video Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction Aljaž Božič, Pablo P

Aljaz Bozic 134 Dec 16, 2022
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.

LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.

donglee 279 Dec 13, 2022
Public repo for the ICCV2021-CVAMD paper "Is it Time to Replace CNNs with Transformers for Medical Images?"

Is it Time to Replace CNNs with Transformers for Medical Images? Accepted at ICCV-2021: Workshop on Computer Vision for Automated Medical Diagnosis (C

Christos Matsoukas 80 Dec 27, 2022
Implementation of gaze tracking and demo

Predicting Customer Demand by Using Gaze Detecting and Object Tracking This project is the integration of gaze detecting and object tracking. Predict

2 Oct 20, 2022
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Payphone 8 Nov 21, 2022
Random-Afg - Afghanistan Random Old Idz Cloner Tools

AFGHANISTAN RANDOM OLD IDZ CLONER TOOLS Install $ apt update $ apt upgrade $ apt

MAHADI HASAN AFRIDI 5 Jan 26, 2022
torchbearer: A model fitting library for PyTorch

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

632 Dec 13, 2022
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

Paul Gavrikov 18 Dec 30, 2022
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

BCMI 49 Jul 27, 2022
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

Alibaba 21 Dec 21, 2022
Image super-resolution through deep learning

srez Image super-resolution through deep learning. This project uses deep learning to upscale 16x16 images by a 4x factor. The resulting 64x64 images

David Garcia 5.3k Dec 28, 2022