GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software
Graph Neural Networks (GNNs) have recently shown to be powerful tools for representing and analyzing graph data. So far GNNs is becoming an increasingly critical role in software engineering including program analysis, type inference, and code representation. In this paper, we introduce GraphGallery, a platform for fast benchmarking and easy development of GNNs based software. GraphGallery is an easy-to-use platform that allows developers to automatically deploy GNNs even with less domain-specific knowledge. It offers a set of implementations of common GNN models based on mainstream deep learning frameworks. In addition, existing GNNs toolboxes such as PyG and DGL can be easily incorporated into the platform. Experiments demonstrate the reliability of implementations and superiority in fast coding. The official source code of GraphGallery is available at https://github.com/EdisonLeeeee/GraphGallery and a demo video can be found at https://youtu.be/mv7Zs1YeaYo.
Code (1)
Tasks
BenchmarkingSimilar Papers 제목 키워드 기반
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search
Neural architecture search (NAS), which automatically designs the architectures of deep neural networks, has achieved breakthrough success over many applications in the past few years. Among different classes of NAS meth…
BenchmarkingGPUNeural Architecture SearchPathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithms
Path planning is a key component in mobile robotics. A wide range of path planning algorithms exist, but few attempts have been made to benchmark the algorithms holistically or unify their interface. Moreover, with the r…
BenchmarkingArena-Web -- A Web-based Development and Benchmarking Platform for Autonomous Navigation Approaches
In recent years, mobile robot navigation approaches have become increasingly important due to various application areas ranging from healthcare to warehouse logistics. In particular, Deep Reinforcement Learning approache…
Autonomous NavigationBenchmarkingDeep Reinforcement Learningreinforcement-learning+3LibOPT: An Open-Source Platform for Fast Prototyping Soft Optimization Techniques
Optimization techniques play an important role in several scientific and real-world applications, thus becoming of great interest for the community. As a consequence, a number of open-source libraries are available in th…
BenchmarkingSystematic Comparison of Path Planning Algorithms using PathBench
Path planning is an essential component of mobile robotics. Classical path planning algorithms, such as wavefront and rapidly-exploring random tree (RRT) are used heavily in autonomous robots. With the recent advances in…
Benchmarking