Loss functions incorporating earth mover’s distance, Pearson Correlation Coefficient, and selective input-driven weighting are presented. Experiments applying these to a passive microwave brightness ...

The Data Science Lab. Autoencoder Anomaly Detection Using PyTorch. Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...

This project focuses on image compression using a convolutional autoencoder. The goal is to compress satellite images from the EuroSAT dataset into a compact representation and reconstruct them with ...

Comparison of the loss function (Mean Squared Error, MSE) deviation for both layers with 10, 30, 50, 100 and 300 hidden nodes. Shown in first + second notes number, respectively ...

In the variational_autoencoder.py example, on line 46 you use: kl_loss = - 0.5 * K.sum(1 + z_log_var - K.square(z_mean) - K.exp(z_log_var), axis=-1) but in your blog ...