|
gptkb:Very_Deep_Super-Resolution
|
mean squared error
|
|
gptkb:VDSR
|
mean squared error
|
|
gptkb:SRGAN
|
adversarial loss
|
|
gptkb:SRResNet
|
mean squared error
|
|
gptkb:Variational_Autoencoder
|
reconstruction loss
|
|
gptkb:Gradient_Boosted_Trees
|
Huber Loss
|
|
gptkb:Wasserstein_GAN_(Arjovsky_et_al.,_2017)
|
gptkb:Wasserstein-1_distance
|
|
gptkb:Variational_Autoencoders
|
reconstruction loss
|
|
gptkb:Variational_Autoencoders
|
gptkb:KL_divergence
|
|
gptkb:UNet_architecture
|
dice loss
|
|
gptkb:DSSM
|
cosine similarity
|
|
gptkb:word2vec
|
hierarchical softmax
|
|
gptkb:variational_autoencoders
|
KL divergence loss
|
|
gptkb:Region_Proposal_Network_(RPN)
|
multi-task loss
|
|
gptkb:VAE_(Variational_Autoencoder)
|
reconstruction loss
|
|
gptkb:Causal_language_modeling
|
Cross-entropy loss
|
|
gptkb:Wasserstein_GAN_(Arjovsky_et_al.,_2017)
|
gptkb:Earth_Mover's_Distance
|
|
gptkb:GCN
|
cross-entropy
|
|
gptkb:U-Net
|
cross-entropy
|
|
gptkb:Deep_Convolutional_GAN
|
Adversarial loss
|