Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...

Cardiovascular Diseases (CVD) are the leading cause of death globally. Non-invasive, cost-effective imaging techniques play a crucial role in early detection and prevention of CVD. Optical Coherence ...

Melville Laboratory for Polymer Synthesis, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K. Melville Laboratory for Polymer Synthesis, Yusuf Hamied ...

Same as traditional autoencoders, VAE architecture has two parts: an encoder and a decoder. Traditional AE models map inputs into a latent-space vector and reconstruct the output from this vector. VAE ...

This repository provides code to accompany the paper: Greener JG, Moffat L and Jones DT, Design of metalloproteins and novel protein folds using variational autoencoders, Scientific Reports 8:16189, ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...