Autoencoders: neural networks in the fight against plagiarism – effective autoencoders

An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction. Recently, the autoencoder concept has become more widely used for learning generative models of data. Some […]

Read More Autoencoders: neural networks in the fight against plagiarism – effective autoencoders