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Autoencoder for Turbulent Flow
The dataset is not explicitly described in the paper, but it is mentioned that the authors used a simple autoencoder to learn a low-order representation of the turbulent flow. -
Importance weighted autoencoders
Importance weighted autoencoders -
Deciphering Autoencoders
Generative Autoencoding of Dropout Patterns -
Optimal Binary Autoencoder with Pairwise Correlations
The dataset used in this paper is a binary autoencoder dataset, where the goal is to learn a binary autoencoder that can reconstruct the input data with the worst-case optimal...
