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4. Discussion The proposed VAE-SURF model introduces a novel hybrid approach for anomaly detection in crowded scenes by synergistically integrating Variational Autoencoders (VAEs) and Speeded-Up ...

This repository contains a Jupyter notebook implementing a Vanilla Variational Autoencoder (VAE) for image generation. The VAE is a powerful generative model that learns to encode images into a latent ...

Abstract: This paper proposes a Multi-scale Dilated Variational Graph Convolutional Autoencoder (MG-VAE) model for gas turbine fault diagnosis. The model integrates a multi-scale dilated convolutional ...

Abstract: This study introduces a novel approach to music generation using a Variational Autoencoder (VAE) model, which incorporates style embeddings for enhanced control over the generated music. The ...

This GitHub repository contains two directories : (1) variational autoencoder (VAE) and (2) denoising convolutional VAE ... Name of the directory where the model parameters are saved.

Our model, known as the constrained subspace variational autoencoder (CS-VAE), successfully models distinct features of the behavioral videos across subjects, as well as continuously varying ...

Recently, we developed a novel nonlinear analysis framework for adult rsfMRI using unsupervised deep generative model – variational autoencoder (VAE) (Kim et al., 2021a). Different from linear ...