Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

A neural autoencoder is essentially a complex mathematical function that predicts its input. All input must be numeric so categorical data must be encoded. Although not theoretically necessary, for ...

MicroCloud Hologram Inc. is advancing the field of quantum computing through its research into Continuous Variable Quantum Neural Networks (CV-QNN), which aim to embed Variational Quantum Circuits ...