IEEE

Deep Graph Convolutional Autoencoder With Conditional Normalizing Flow for Power Distribution Systems Fault Classification and Location

Abstract: Accurate fault classification and location are critical to ensure the reliability and resilience of large-scale power distribution systems (PDSs). The existing data-driven works in this area ...
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 ...
GitHub

PyTorch Essential Training: Working with Images

This is the repository for the LinkedIn Learning course PyTorch Essential Training: Working with Images. The full course is available from LinkedIn Learning. Machine learning developers and data ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

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.