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Found 5 papers, 1 papers with code
S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction
We address the video prediction task by putting forth a novel model that combines (i) our recently proposed hierarchical residual vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel spatiotemporal PixelCNN (ST-PixelCNN).
Hierarchical Residual Learning Based Vector Quantized Variational Autoencoder for Image Reconstruction and Generation
We propose a multi-layer variational autoencoder method, we call HR-VQVAE, that learns hierarchical discrete representations of the data.
STEP-GAN: A Step-by-Step Training for Multi Generator GANs with application to Cyber Security in Power Systems
In this study, we introduce a novel unsupervised countermeasure for smart grid power systems, based on generative adversarial networks (GANs).
Statistical feature embedding for heart sound classification
In this study, an approach is proposed for normal/abnormal heart sound classification on the Physionet challenge 2016 dataset.
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