Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...

Herein, we present Rapidae, an open-source Python library designed to ease the use, development, and benchmarking of autoencoder models ... supporting a seamless transition between TensorFlow, PyTorch ...

Then, MSM and TPT are constructed to obtain the ensemble of pathways, and a deep learning architecture named the variational autoencoder (VAE) is used to learn the spatial distributions of kinetic ...

Abstract: A complex-valued autoencoder neural network ca-pable of compressing & denoising radio frequency signals with arbitrary model scaling is proposed. Complex-valued time sam-ples received with ...

We use torchinfo to have an output of the model's architecture similar to keras' model.summary(). It's not necessary for the code to run. All the relevant information for the training procedure, such ...

This article explains how to use a PyTorch neural autoencoder to find anomalies in a dataset. A good way to see where this article is headed is to take a look at the screenshot of a demo program in ...