Conditional autoencoder is a semi-supervised model that learns an abstract representation of the data and provides conditional reconstruction capabilities. Such models are suited to problems with ...

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The repository has many scripts implanting Multi-Instance Conditional Autoencoder over two images datasets (mnist, cifar10) and two audio datasets (celebrity and Javanese). Our approach and the ...

Accent plays a significant role in speech communication, influencing one's capability to understand as well as conveying a person's identity. This paper introduces a novel and efficient framework for ...

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 ...

This study examines the performance of Conditional Variational Autoencoder (CVAE) in handwritten digit recognition. Using the MNIST dataset, two variants of the CVAE models — convolutional and ...

Graph-Based Conditional Variational Autoencoder. Here, small molecules are described as mathematical graphs composed of nodes and edges representing atoms and chemical bonds, respectively. In the ...