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Experimentally realized memristive memory augmented neural network
[article]
2022
arXiv
pre-print
Lifelong on-device learning is a key challenge for machine intelligence, and this requires learning from few, often single, samples. Memory augmented neural network has been proposed to achieve the goal, but the memory module has to be stored in an off-chip memory due to its size. Therefore the practical use has been heavily limited. Previous works on emerging memory-based implementation have difficulties in scaling up because different modules with various structures are difficult to integrate
arXiv:2204.07429v1
fatcat:5xvdijrhb5bple54gvcpnapmum