Memory-Augmented Graph Neural Networks: A Brain-Inspired Review
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Abstract (arXiv)
We provide a comprehensive review of the existing literature on memory-augmented GNNs. We review these works through the lens of psychology and neuroscience, which has several established theories on how multiple memory systems and mechanisms operate in biological brains. We propose a taxonomy of memory-augmented GNNs and a set of criteria for comparing their memory mechanisms. We also provide critical discussions on the limitations of these works. Finally, we discuss the challenges and future directions for this area.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 56 of its 108 references that are in the map. First posted on arXiv 22 Sep 2022.
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56 of 108 references.
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38 more
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