IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

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 ...
IEEE

Fault Detection Method for Power Conversion Circuits Using Thermal Image and Convolutional Autoencoder

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 ...
GitHub

vae-cnn

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 ...
Scientific Research Publishing

Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J. et al. (2019). PyTorch: An Imperative Style, High-Performance Deep Learning Library. Advances in Neural Information ...

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 ...
GitHub

ElvianElvy/Graph-Convolutional-LSTM-Spatial-Temporal-GNN-

A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...