Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.

A fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power ...

PyTorch-based pipeline that trains a convolutional variational autoencoder on cat images, optionally tunes hyperparameters with Ray Tune, and samples new images by fitting a Gaussian Mixture Model in ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...

Due to a production error, there was an error regarding the affiliation for Somayeh Makouei. Instead of having affiliation 2, they should have affiliation 1 ...

1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran 2 College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, United Kingdom ...