https://www.selleckchem.com/pr....oducts/jnk-inhibitor
Encoder-decoder recurrent neural network models (RNN Seq2Seq) have achieved success in ubiquitous areas of computation and applications. They were shown to be effective in modeling data with both temporal and spatial dependencies for translation or prediction tasks. In this study, we propose an embedding approach to visualize and interpret the representation of data by these models. Furthermore, we show that the embedding is an effective method for unsupervised learning and can be utilized to estimate the optimality of model
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