[1] D. P. Kingma and M. Welling, “Auto-Encoding Variational Bayes,” in International Conference on Learning Representations (ICLR), 2014, p. Arxiv: 1312.6114v10 ...

A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data ...

To overcome such challenges, we propose a variational autoencoder architecture-based deep metric learning, which is optimized using a novel loss function combining a statistical distance triplet loss ...

we propose a multi-domain variational autoencoder framework consisting of multiple domain-specific branches and a latent space shared across all branches for cross-domain information exchange. The ...

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 ...

We propose a method for generating an electrocardiogram (ECG) signal for one cardiac cycle using a variational autoencoder ... we get 400 neurons which represent the restored ECG. As a loss function ...