#计算机科学#Python package built to ease deep learning on graph, on top of existing DL frameworks.
翻译 - 在现有DL框架之上构建的Python软件包，用于简化图上的深度学习。
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
Python package for graph neural networks in chemistry and biology
Materials for DGL hands-on tutorial in WWW 2020
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Delphi / Pascal OpenGL header translation (including WGL and GLX)
DGL tutorial in KDD 2019
#计算机科学#Repository for benchmarking graph neural networks
翻译 - 基准图神经网络的存储库
Code for paper "EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning"
The official repo is https://github.com/dmlc/dgl . THIS IS A FORK.
翻译 - 官方仓库是https://github.com/dmlc/dgl。这是叉子。
Use Amazon SageMaker and Deep Graph Library (DGL) for Fraud Detection in Networks
Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'
Graphiler is a compiler stack built on top of DGL and TorchScript which compiles GNNs defined using user-defined functions (UDFs) into efficient execution plans.
An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from...