To address this limitation, we introduce a novel generative model that integrates the principles of variational autoencoders (VAEs) with adversarial training techniques. Our model consists of a ...

Variational Autoencoder (VAE) project using PyTorch, showcasing generative modeling through Fashion MNIST data encoding, decoding, and latent space exploration. Explore tasks like model implementation ...

Train a Variational Auto-encoder using facenet-based perceptual loss similar to the paper "Deep Feature Consistent Variational Autoencoder". ... The last batch for the above training looked like this: ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

Deep neural networks (DNNs) have demonstrated exceptional performance across a variety of applications, yet they require substantial computing and power resources. In contrast, Spiking Neural Networks ...