Reinforcement learning research in humans and other species indicates that rewards are represented in a context-dependent manner. More specifically, reward representations seem to be normalized as a ...

Several applications including text-to-speech re-quire some normalized format of non-standard words in various domains such as numbers, dates, and currencies and in various human languages. The ...

Normalization is an essential step in the analysis of high-throughput data. Multi-sample global normalization methods, such as quantile normalization, have been successfully used to remove technical ...

While LVS normalization requires setting in advance a number for the fraction of genes to be considered as non-differentially expressed, with values in the range 40–60% 45, Cross-Correlation and NVAS ...

In this repository we will provide the code for the paper Normalization of Histological Stains using Deep Convolutional Features. For more information, visit the ...

For many practical computer vision applications, the learned models usually have high performance on the datasets used for training but suffer from significant performance degradation when deployed in ...