Python Skeletal-GNN Resources

On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks We provide the code (in PyTorch) and datasets for our paper "On Size-Orient

HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv

DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

Equivariant Graph Neural Network for Atomic Multipoles Description Repository for the Model used in the publication 'Learning Atomic Multipoles: Predi

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN

SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars

decentralized-gnn A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes. De

Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks This is the official code for DyReg model inroduced in Discovering Dyna

(中文文档|简体中文|English) 什么是推荐系统? 推荐系统是在互联网信息爆炸式增长的时代背景下，帮助用户高效获得感兴趣信息的关键； 推荐系统也是帮助产品最大限度吸引用户、留存用户、增加用户粘性、提高用户转化率的银弹。 有无数优秀的产品依靠用户可感知的推荐系统建立了良好的口碑，也有无数的公司依

GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs [Paper, Slides, Video Talk] at USENIX OSDI'21 @inproceedings{GNNAdvisor, title=

GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma

Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

SkeletonNet This repository constains the codes and ShapeNetV1-Surface-Skeleton,ShapNetV1-SkeletalVolume and 2d image datasets ShapeNetRendering. Plea

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

GRecX A Fair Benchmark for GNN-based Recommendation Preliminary Comparison DiffNet-Yelp dataset (featureless) Algo nDCG@5 nDCG@10 nDCG@15 MF 0.158707

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

MIA GNN Project Starter If you meet the version mismatch error for Lasagne library, please use following command to upgrade Lasagne library. pip insta

FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (

GCE-GNN Code This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation. Requirement

Basic Information: This code is released for the papers: Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Dif

An index of recommendation algorithms that are based on Graph Neural Networks.

Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu

Magnetic Graph Convolutional Networks About The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via M

SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features

GNNLens2 is an interactive visualization tool for graph neural networks (GNN).

VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto

Single Node Injection Attack against Graph Neural Networks This repository is our Pytorch implementation of our paper: Single Node Injection Attack ag

Geometric Vector Perceptron Code to accompany Learning from Protein Structure with Geometric Vector Perceptrons by B Jing, S Eismann, P Suriana, RJL T

SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s

CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur

SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an

ncem Features Repository for the manuscript Fischer, D. S., Schaar, A. C. and Theis, F. Learning cell communication from spatial graphs of cells. 2021

Distance-encoding for GNN design This repository is the official PyTorch implementation of the DEGNN and DEAGNN framework reported in the paper: Dista

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

Expressive Power of Invariant and Equivaraint Graph Neural Networks In this repository, we show how to use powerful GNN (2-FGNN) to solve a graph alig

This repo includes the Pytorch-Geometric implementation of a series of Graph Neural Network (GNN) based fake news detection models. All GNN models are implemented and evaluated under the User Preference-aware Fake News Detection (UPFD) framework. The fake news detection problem is instantiated as a graph classification task under the UPFD framework.

This repository provides an end-to-end library for automatic character rigging and blend shapes generation as well as a visualization tool. It is based on our work Learning Skeletal Articulations with Neural Blend Shapes that is published in SIGGRAPH 2021.

This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).

QA-GNN: Question Answering using Language Models and Knowledge Graphs This repo provides the source code & data of our paper: QA-GNN: Reasoning with L

Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind

Documentation | External Resources | Datasets PyTorch Geometric Temporal is a temporal (dynamic) extension library for PyTorch Geometric. The library