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A collection of important graph embedding, classification and representation learning papers with implementations for vibe coders.
A PyTorch library for processing spatiotemporal graph data using neural machine learning models.
A distributed graph deep learning framework for building graph-based AI models and applications.
A collection of must-read papers on network representation learning (NRL) and network embedding (NE)
An open-source package for network embedding, a technique for learning low-dimensional representations of nodes in a network.
A Python library for learning graph embeddings and applying them to tasks like link prediction.
A high-performance graph embedding system that supports CUDA and can be used for machine learning and knowledge graph applications.
A heterogeneous graph neural network library for advanced graph representation learning.
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