|
gptkb:LambdaMART
|
listwise loss
|
|
gptkb:pix2pix_framework
|
L1 loss
|
|
gptkb:Gatys_et_al._neural_style_transfer
|
style loss
|
|
gptkb:VAE
|
reconstruction loss
|
|
gptkb:Least_Squares_Generative_Adversarial_Network
|
least squares loss
|
|
gptkb:DSSM
|
cosine similarity
|
|
gptkb:V-Net
|
Dice loss
|
|
gptkb:Variational_Autoencoders
|
reconstruction loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
reconstruction loss
|
|
gptkb:U-Net
|
cross-entropy
|
|
gptkb:BYOL
|
mean squared error
|
|
gptkb:WGAN
|
Wasserstein loss
|
|
gptkb:Deep_Convolutional_GAN
|
Adversarial loss
|
|
gptkb:Supervised_learning
|
Measures prediction error
|
|
gptkb:Graph_Attention_Networks
|
cross-entropy
|
|
gptkb:SRGAN
|
perceptual loss
|
|
gptkb:UNet_architecture
|
dice loss
|
|
gptkb:Gradient_Boosted_Trees
|
Huber Loss
|
|
gptkb:Very_Deep_Super-Resolution
|
mean squared error
|
|
gptkb:ListNet
|
listwise loss
|