along with bayesian search, it also employs tree-structured parzen. firstly, we define our objective function, which also has trial as an argument( to display the information after each trial). in our ...

The function train_vae is responsible for building and training the VAE (Variational Autoencoder) model. It takes in the latent_dim parameter along with other hyperparameters of the model. The ...

We propose an algorithm, guided variational autoencoder (Guided-VAE), that is able to learn a controllable generative model by performing latent representation disentanglement learning. The learning ...

In the neuroimaging and brain mapping communities, researchers have proposed a variety of computational methods to map functional brain networks (FBNs). Recently, it has been proven that deep learning ...

Besides, the loss function of the variational autoencoder is revised and improved. The aim is to learn feature representations with fewer image features to obtain more accurate results. (2) In the ...