Mar 1, 2021 · A comprehensive library for graph deep learning that allows researchers and practitioners to conduct experiments, compare methods, and build applications with ...

Apr 30, 2023 · A comprehensive library for graph deep learning that allows researchers and practitioners to conduct experiments, compare methods, and build applications with ...

CogDL is a graph deep learning toolkit that allows researchers and developers to easily train and compare baseline or customized models for node classification, ...

Apr 30, 2023 · Deep Graph. Library (DGL) [91] is an efcient and scalable package for deep learning on graphs, which provides several APIs allowing arbitrary.

In CogDL, we propose a unified design for the training and evaluation of GNN models for various graph tasks, making it unique among existing graph learning ...

CogDL is an extensive Toolkit for Graph Neural Networks, which provides lots of effective and efficient solutions for real-world problems especially those ...

Aug 15, 2024 · It currently contains more than 10 attack algorithms and 8 defense algorithms in image domain and 9 attack algorithms and 4 defense algorithms ...

This paper proposes a unified design for the training loop of graph neural network (GNN) models, making it unique among existing graph learning libraries, ...

The new v0.1.2 release includes a pre-training task, many examples, OGB datasets, some knowledge graph embedding methods, and some graph neural network models.

Missing: Comprehensive Library