CNN Autoencoder on Fashion-MNIST for Image Reconstruction and Dimensionality Reduction Description: This part implements a Convolutional Autoencoder (CAE) on the Fashion-MNIST dataset, primarily for ...

RealAmplitude, when used as an autoencoder, has limitations in compressing qubits due to its restriction to real amplitudes, neglecting complex values. This results in certain errors in decompression ...

Towards Green VAE: A Light Pixel-weighting Technique to Enhance Variational AutoEncoder Abstract: Variational autoencoders (VAEs) has been a popular generative model for its effectiveness, ...

Entrenamiento y testeo de un autoencoder para el dataset MNIST para identificar números escritos a mano - Issues · Apolo5102/Autoencoder---MNIST ...

Imaging mass spectrometry (IMS) is a technique for simultaneously acquiring the expression and distribution of molecules on the surface of a sample, and it plays a crucial role in spatial omics ...

The autoencoder model used on the MNIST experiments consists of one convolutional layer with 32 filters and rectified linear unit (ReLU) activations, followed by a max pooling layer.

A spiking autoencoder is used to generate compressed spatio-temporal spike maps of images (MNIST). A spiking audiocoder then learns to map audio samples to these compressed spike map representations, ...