Balancing Entropy and Recall Rates for AutoEncoders

Autoencoders are neural network architectures that are used to learn a compact representation of input data, called the encoding, and then reconstruct the input data from this encoding. Autoencoders can be used to process point cloud data, which is a set of points in space that represent the surface of an object, as well as…
Read more