|
gptkb:VAE
|
reconstruction loss
|
|
gptkb:pix2pix_framework
|
L1 loss
|
|
gptkb:Variational_Autoencoder
|
reconstruction loss
|
|
gptkb:UNet_architecture
|
dice loss
|
|
gptkb:SRGAN
|
adversarial loss
|
|
gptkb:VDSR
|
mean squared error
|
|
gptkb:LambdaMART
|
pairwise loss
|
|
gptkb:Supervised_learning
|
Measures prediction error
|
|
gptkb:UNet_architecture
|
cross-entropy
|
|
gptkb:Pix2Pix
|
L1 loss
|
|
gptkb:GCN
|
cross-entropy
|
|
gptkb:Denoising_autoencoder
|
Reconstruction loss
|
|
gptkb:Gatys_et_al._neural_style_transfer
|
content loss
|
|
gptkb:LambdaMART
|
listwise loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
reconstruction loss
|
|
gptkb:Logistic_regression
|
Log loss
|
|
gptkb:variational_autoencoders
|
KL divergence loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
gptkb:KL_divergence
|
|
gptkb:Variational_Autoencoder
|
gptkb:Kullback-Leibler_divergence
|
|
gptkb:Wasserstein_GAN_(Arjovsky_et_al.,_2017)
|
gptkb:Wasserstein-1_distance
|