127 Open source projects that are alternatives of or similar to Spectral-Designed-Graph-Convolutions

links to conference publications in graph-based deep learning

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

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

Graph Neural Network Library for PyTorch

Summary of open source code for deep learning models in the field of traffic prediction

StellarGraph - Machine Learning on Graphs

Representation Learning on Graphs with Jumping Knowledge Networks

A reading list for deep graph learning acceleration.

Tutorials for Machine Learning on Graphs

A distributed graph deep learning framework.

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Code and resources on scalable and efficient Graph Neural Networks

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

PyTorch implementation of our paper "Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing" (NAACL19)

This is a paper list about Resource Allocation in Network Functions Virtualization (NFV) and Software-Defined Networking (SDN).

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

Graph-based machine learning for chemical property prediction

An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).

ACL 2018: Dating Documents using Graph Convolution Networks

Code for the BMVC paper (http://bmvc2018.org/contents/papers/1003.pdf)

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Supervised community detection with line graph neural networks

Message Passing Neural Networks for Simplicial and Cell Complexes

⚡ Using deep learning (MLP, CNN, Graph CNN) to classify text in TensorFlow.

The implement of GNN based on Pytorch

Code & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"

A peak-fitting tool based on MATLAB for spectroscopic data analysis.

Locally Private Graph Neural Networks (ACM CCS 2021)

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

Probabilistic Type Inference using Graph Neural Networks

Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)

Tensorflow Implementation of the paper "Topology Adaptive Graph Convolutional Networks" (Du et al., 2017)

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

Smart Contract Vulnerability Detection Using Graph Neural Networks (IJCAI-20 Accepted)

TypeDB-ML is the Machine Learning integrations library for TypeDB

A curated list of awesome graph & self-supervised-learning-based recommendation.

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

A list of data mining and machine learning papers that I implemented in 2019.

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

This is a Pytorch implementation of GraphLIME

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

[COLING 2020] Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

Official repository for the paper "Learning Local Neighboring Structure for Robust 3D Shape Representation"

A spherical CNN for weather forecasting

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

A spherical convolutional neural network for cosmology (TFv1).

Representing Long-Range Context for Graph Neural Networks with Global Attention

Reimplementation of Graph Embedding methods by Pytorch.

[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

Chainer implementation of 'Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering' (https://arxiv.org/abs/1606.09375)

AAAI'21: Data Augmentation for Graph Neural Networks