Higher-order Interpretations of Deepcode, a Learned Feedback Code
We present an interpretation of Deepcode, a learned feedback code that showcases higher-order error correction relative to an earlier interpretable model. By interpretation, we mean succinct analytical encoder and decoder expressions (albeit with learned parameters) in which the role of feedback in...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
21.08.2024
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Subjects | |
Online Access | Get full text |
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Summary: | We present an interpretation of Deepcode, a learned feedback code that
showcases higher-order error correction relative to an earlier interpretable
model. By interpretation, we mean succinct analytical encoder and decoder
expressions (albeit with learned parameters) in which the role of feedback in
achieving error correction is easy to understand. By higher-order, we mean that
longer sequences of large noise values are acted upon by the encoder (which has
access to these through the feedback) and used in error correction at the
decoder in a two-stage decoding process. |
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DOI: | 10.48550/arxiv.2408.11907 |