PyGDA: A Python Library for Graph Domain Adaptation
Graph domain adaptation has emerged as a promising approach to facilitate
knowledge transfer across different domains. Recently, numerous models have
been proposed to enhance their generalization capabilities in this field.
However, there is still no unified library that brings together existing
techniques and simplifies their implementation. To fill this gap, we introduce
PyGDA, an open-source Python library tailored for graph domain adaptation. As
the first comprehensive library in this area, PyGDA covers more than 20 widely
used graph domain adaptation methods together with different types of graph
datasets. Specifically, PyGDA offers modular components, enabling users to
seamlessly build custom models with a variety of commonly used utility
functions. To handle large-scale graphs, PyGDA includes support for features
such as sampling and mini-batch processing, ensuring efficient computation. In
addition, PyGDA also includes comprehensive performance benchmarks and
well-documented user-friendly API for both researchers and practitioners. To
foster convenient accessibility, PyGDA is released under the MIT license at
https://github.com/pygda-team/pygda, and the API documentation is
https://pygda.readthedocs.io/en/stable/.
67d6471368b6209d9ad9f7f2
Zhen Zhang
claimed_verified
2025-03-16T21:12:18.394Z
67d645ef9b5e492b00e79af9
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/AW_0U1377safcLfIIwgA5.png
Zhen Zhang
user
zhenzhangcs
67d6471368b6209d9ad9f7f3
Meihan Liu
67d6471368b6209d9ad9f7f4
Bingsheng He
PyGDA: A Python Library for Graph Domain Adaptation
Graph domain adaptation has emerged as a promising approach to facilitate
knowledge transfer across different domains. Recently, numerous models have
been proposed to enhance their generalization capabilities in this field.
However, there is still no unified library that brings together existing
techniques and simplifies their implementation. To fill this gap, we introduce
PyGDA, an open-source Python library tailored for graph domain adaptation. As
the first comprehensive library in this area, PyGDA covers more than 20 widely
used graph domain adaptation methods together with different types of graph
datasets. Specifically, PyGDA offers modular components, enabling users to
seamlessly build custom models with a variety of commonly used utility
functions. To handle large-scale graphs, PyGDA includes support for features
such as sampling and mini-batch processing, ensuring efficient computation. In
addition, PyGDA also includes comprehensive performance benchmarks and
well-documented user-friendly API for both researchers and practitioners. To
foster convenient accessibility, PyGDA is released under the MIT license at
https://github.com/pygda-team/pygda, and the API documentation is
https://pygda.readthedocs.io/en/stable/.
PyGDA is an open-source library for graph domain adaptation that includes over 20 methods and supports large-scale graph processing efficiently.
graph domain adaptation PyGDA graph datasets sampling mini-batch processing performance benchmarks API documentation