IEEE

Tree Variational Autoencoder for Code

Abstract: Autoencoder models of source code are an emerging alternative to autoregressive large language models with important benefits for genetic improvement of software. We hypothesize that encoder ...
Scientific Research Publishing

Variational Auto-Encoder and Speeded-Up Robust Features Hybrid Model for Anomaly Detection and Localization in Video Sequence with Scale Variation ()

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...
GitHub

Variational Autoencoder (VAE) for Image Generation: A Comparative Study

This repository contains a comprehensive implementation of Variational Autoencoders (VAEs) applied to two different image datasets: CIFAR-10 and Fashion-MNIST. The project demonstrates how dataset ...
GitHub

ti2ni1m/Image-Generation-with-Conditional-Variational-Autoencoder-C-VAE-and-Conditional-GAN-C-GAN-

In this project, I aim to create a set of images of Kuzushiji Japanese characters via the Kuzushiji-49 dataset using 2 graphical models which are Conditional-Variational Autoencoder(C-VAE), and ...