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Jin, W., Barzilay, R. and Jaakkola, T. (2018) Junction Tree Variational Autoencoder for Molecular Graph Generation. International Conference on Machine Learning, Stockholm, 10-15 July 2018, 2323-2332.

Manuel Lopez-Martin, Belen Carro, Antonio Sanchez-Esguevillas and Jaime Lloret, "Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT" About.

This GitHub repository contains two directories : (1) variational autoencoder (VAE) and (2) denoising convolutional VAE (DCVAE). This contains programs for VAE and DCVAE models used in our work. For ...

Schematic diagram of Dear-DIA. view more . ... Next, Dear-DIA uses a variational autoencoder to extract the peak features of fragment ions and maps the features into Euclidean space, ...

A technical paper titled “Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques” was published by researchers at Commonwealth Scientific and ...

In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random variable is ...

Schematic representation of a variational autoencoder with predictor network. A common example of an activation function is the sigmoid ... Exploring factor structures using variational autoencoder in ...