|
gptkb:convolutional_neural_network
|
binary cross-entropy
|
|
gptkb:Conditional_Generative_Adversarial_Network
|
adversarial loss
|
|
gptkb:SRGAN
|
adversarial loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
gptkb:KL_divergence
|
|
gptkb:RankNet
|
cross-entropy loss
|
|
gptkb:Wasserstein_GAN_(Arjovsky_et_al.,_2017)
|
gptkb:Wasserstein-1_distance
|
|
gptkb:GANs
|
adversarial loss
|
|
gptkb:pix2pix_framework
|
adversarial loss
|
|
gptkb:UNet_architecture
|
cross-entropy
|
|
gptkb:Variational_autoencoder
|
reconstruction loss
|
|
gptkb:variational_autoencoders
|
reconstruction loss
|
|
gptkb:SAMME
|
exponential loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
reconstruction loss
|
|
gptkb:V-Net
|
Dice loss
|
|
gptkb:BYOL
|
mean squared error
|
|
gptkb:word2vec
|
negative sampling
|
|
gptkb:WGAN-GP
|
Wasserstein loss with gradient penalty
|
|
gptkb:Least_Squares_Generative_Adversarial_Network
|
least squares loss
|
|
gptkb:generative_adversarial_networks
|
minimax loss
|
|
gptkb:Variational_Autoencoder
|
reconstruction loss
|