Loss Functions

Loss Functions are used to frame the problem to be optimized within deep learning. Below you will find a continuously updating list of (specialized) loss functions for neutral networks.

METHOD YEAR PAPERS
Cycle Consistency Loss
2017 154
GAN Least Squares Loss
2016 148
Focal Loss
2017 139
GAN Hinge Loss
2017 46
InfoNCE
2018 31
WGAN-GP Loss
2017 19
VGG Loss
2016 18
CTC Loss
2000 17
ArcFace
2018 15
NT-Xent
2016 5
Lovasz-Softmax
2018 3
Balanced L1 Loss
2019 2
Supervised Contrastive Loss
2020 1
Dynamic SmoothL1 Loss
2020 1
Self-Adjusting Smooth L1 Loss
2019 1