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Updated: Jul 5, 2025

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
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在多重假设测试中转移学习

Stefano Cabras1, María Eugenia Castellanos Nueda2

  • 1Department of Statistics, University Carlos III of Madrid, 28903 Madrid, Spain.

Entropy (Basel, Switzerland)
|January 22, 2024
PubMed
概括

这项研究引入了一种新的卷积神经网络 (CNN) 方法,用于多重假设测试 (MHT),提高精度和稳定性. 该方法将CNN与贝叶斯推理相结合,用于改进基因组学中的序列分析.

关键词:
RNA-seq实验中的实验贝叶斯因素是贝叶斯因素的一个组成部分.深度学习是一种深度学习.不适当的先验.客观的贝叶斯推论 客观的贝叶斯推论随机的顺序是随机的顺序.

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