Generate Digit Images on NVIDIA GPU Using Variational Autoencoder
This example shows how to generate CUDA® MEX for a trained variational autoencoder (VAE) network. The example illustrates: Generation of hand-drawn digit images in the style of the …
Vision Models — NVIDIA NeMo Framework User Guide
May 17, 2025 · AutoencoderKL (Variational Autoencoder with KL loss: The AutoencoderKL model is a Variational Autoencoder (VAE) equipped with KL loss, introduced in the paper Auto …
[2102.12037] Conditional Image Generation by Conditioning Variational …
Feb 24, 2021 · We present a conditional variational auto-encoder (VAE) which, to avoid the substantial cost of training from scratch, uses an architecture and training objective capable of …
NVAE | Proceedings of the 34th International Conference on …
Dec 6, 2020 · We propose Nouveau VAE (NVAE), a deep hierarchical VAE built for image generation using depth-wise separable convolutions and batch normalization. NVAE is …
Title: Generating Diverse High-Fidelity Images with VQ-VAE-2
Jun 2, 2019 · We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE) models for large scale image generation. To this end, we scale and enhance the autoregressive priors …
Image Super-Resolution With Deep Variational Autoencoders
Mar 17, 2022 · VAE-based models have often been criticised for their feeble generative performance, but with new advancements such as VDVAE, there is now strong evidence that …
NVAE: A Deep Hierarchical Variational Autoencoder | Research - NVIDIA
Jul 8, 2020 · We propose Nouveau VAE (NVAE), a deep hierarchical VAE built for image generation using depth-wise separable convolutions and batch normalization. NVAE is …
Generate Images Using Variational Autoencoder (VAE)
Apr 18, 2020 · In this post, we want to introduce the variational autoencoder (VAE) and use it to generate new images of handwritten digits by using MNIST as training data. VAE is a …
A Contrastive Learning Approach for Training Variational ... - NVIDIA
Nov 18, 2021 · Variational autoencoders (VAEs) are one of the powerful likelihood-based generative models with applications in many domains. However, they struggle to generate …
The Official PyTorch Implementation of "NVAE: A Deep ... - GitHub
NVAE is a deep hierarchical variational autoencoder that enables training SOTA likelihood-based generative models on several image datasets. NVAE is built in Python 3.7 using PyTorch …
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