THUMNLab/awesome-auto-graph-learning
A paper collection about automated graph learning
This is a curated collection of academic papers focused on automated graph learning. It brings together research on techniques like hyper-parameter optimization (HPO) and neural architecture search (NAS) specifically for graph-based machine learning models. Researchers and practitioners working with graph data will find this useful for staying updated on the latest advancements in designing and optimizing graph neural networks.
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Use this if you are a researcher or advanced practitioner interested in the cutting-edge methods for automatically designing and tuning machine learning models that operate on complex network or graph structures.
Not ideal if you are looking for an off-the-shelf software tool to apply graph machine learning without delving into the underlying research and model architecture.
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Jun 08, 2024
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