Muhammed Fatih Balın

Concrete Autoencoders: Differentiable Feature Selection and Reconstruction

We introduce the concrete autoencoder, an end-to-end differentiable method for global feature selection, which efficiently identifies a subset of the most informative features and simultaneously learns a neural network to reconstruct the input data from the selected features. Our method is unsupervi…