PyTorch Geometric Temporal DocumentationΒΆ

PyTorch Geometric Temporal is an temporal graph neural network extension library for PyTorch Geometric. It builds on open-source deep-learning and graph processing libraries. PyTorch Geometric Temporal consists of state-of-the-art deep learning and parametric learning methods to process spatio-temporal signals. It is the first open-source library for temporal deep learning on geometric structures. First, it provides discrete time graph neural networks on dynamic and static graphs. Second, it allows for spatio-temporal learning when the time is represented continuously without the use of discrete snapshots. Implemented methods cover a wide range of data mining (WWW, KDD), artificial intelligence and machine learning (AAAI, ICONIP, ICLR) conferences, workshops, and pieces from prominent journals.

>@misc{pytorch_geometric_temporal,
       author = {Benedek, Rozemberczki and Paul, Scherer},
       title = {{PyTorch Geometric Temporal}},
       year = {2020},
       publisher = {GitHub},
       journal = {GitHub repository},
       howpublished = {\url{https://github.com/benedekrozemberczki/pytorch_geometric_temporal}},
}