![Revolutionizing M-TGNNs: DistTGL Offers Scalable Training Solution for Memory-Based Temporal Neural Networks](https://www.cjco.com.au/wp-content/uploads/ixidM3w0NDIyMzJ8MHwxfHJhbmRvbXx8fHx8fHx8fDE2OTYxOTg2NjR8ixlibrb-4.0.3fitcropw1800q70-768x511.jpg)
Revolutionizing M-TGNNs: DistTGL Offers Scalable Training Solution for Memory-Based Temporal Neural Networks
Temporal Graph Neural Networks (TGNNs) have become a vital tool for learning static graph representations. Their brilliance in high accuracy tasks such as dynamic node classification and temporal link prediction on versatile dynamic graphs is commonly recognized in this cognitive computing age. Despite their impressive performance, traditional TGNNs haven't been without limitations. One significant setback…
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