Universal Recurrent Event Memories for Streaming Data
In this paper, we propose a new event memory architecture (MemNet) for recurrent neural networks, which is universal for different types of time series data such as scalar, multivariate or symbolic. Unlike other external neural memory architectures, it stores key-value pairs, which separate the info...
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Main Authors | , |
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Format | Journal Article |
Language | English |
Published |
28.07.2023
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Subjects | |
Online Access | Get full text |
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