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How to transfer algorithmic reasoning knowledge to learn new algorithms?
Due to the fundamental differences between algorithmic reasoning knowledge and feature extractors such as used in Computer Vision or NLP, we hypothesise that standard transfer techniques will not be sufficient to achieve systematic generalisation.
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention
Through many recent advances in graph representation learning, performance achieved on tasks involving graph-structured data has substantially increased in recent years---mostly on tasks involving node-level predictions.
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