|
gptkb:VAE
|
reconstruction loss
|
|
gptkb:Gradient_Boosted_Trees
|
Huber Loss
|
|
gptkb:Very_Deep_Super-Resolution
|
mean squared error
|
|
gptkb:U-Net
|
cross-entropy
|
|
gptkb:VDSR
|
mean squared error
|
|
gptkb:GCN
|
cross-entropy
|
|
gptkb:LambdaMART
|
pairwise loss
|
|
gptkb:Variational_autoencoder
|
gptkb:Kullback-Leibler_divergence
|
|
gptkb:GANs
|
adversarial loss
|
|
gptkb:Variational_Autoencoder
|
reconstruction loss
|
|
gptkb:U-Net
|
dice loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
reconstruction loss
|
|
gptkb:UNet_architecture
|
cross-entropy
|
|
gptkb:Variational_Autoencoders
|
gptkb:KL_divergence
|
|
gptkb:generative_adversarial_networks
|
minimax loss
|
|
gptkb:LSGAN
|
Least squares loss
|
|
gptkb:variational_autoencoders
|
reconstruction loss
|
|
gptkb:VAE
|
gptkb:KL_divergence
|
|
gptkb:TransR
|
margin-based ranking loss
|
|
gptkb:Gatys_et_al._neural_style_transfer
|
style loss
|