Deepcode（一种学习型反馈码）的高阶解释
Higher-order Interpretations of Deepcode, a Learned Feedback Code
AI总结：
本文提出了对学习型反馈码Deepcode的高阶解释，通过简洁的解析型编解码器表达式揭示了反馈在两阶段解码纠错中的作用。
摘要：
我们提出了对Deepcode（一种学习型反馈码）的解释，该解释展示了相对于早期可解释模型的高阶纠错能力。所谓解释，是指简洁的解析型编解码器表达式（尽管带有学习参数），其中反馈在实现纠错中的作用易于理解。所谓高阶，是指编码器（通过反馈获取这些信息）会处理长序列的大噪声值，并在两阶段解码过程中将其用于解码器的纠错。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
