Methods › General › Loss Functions
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.
Methods
All 43 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.
| Focal Loss | – | 461 |
| Cycle Consistency Loss | – | 448 |
| Triplet Loss | – | 424 |
| GAN Least Squares Loss | – | 421 |
| InfoNCE | – | 418 |
| NT-Xent Normalized Temperature-scaled Cross Entropy Loss | – | 251 |
| FLIP | – | 237 |
| GAN Hinge Loss | – | 167 |
| Dice Loss | – | 108 |
| ArcFace Additive Angular Margin Loss | – | 94 |
| Huber loss | – | 77 |
| Supervised Contrastive Loss | – | 76 |
| Adaptive Loss Adaptive Robust Loss | – | 73 |
| Early exiting Early exiting using confidence measures | – | 66 |
| WGAN-GP Loss | – | 65 |
| CTC Loss Connectionist Temporal Classification Loss | – | 47 |
| VGG Loss | – | 37 |
| Varifocal Loss | – | 8 |
| Balanced L1 Loss | – | 7 |
| uPIT utterance level permutation invariant training | – | 7 |
| ElasticFace Elastic Margin Loss for Deep Face Recognition | – | 5 |
| HAPPIER Hierarchical Average Precision training for Pertinent ImagE Retrieval | – | 5 |
| Lovasz-Softmax | – | 5 |
| Generalized Focal Loss | – | 4 |
| Nebula | – | 4 |
| Rank-based Loss Rank-based loss | – | 4 |
| Dynamic SmoothL1 Loss | – | 3 |
| Seesaw Loss | – | 3 |
| Multi Loss ( BCE Loss + Focal Loss ) + Dice Loss | – | 2 |
| ProxyAnchorLoss Proxy Anchor Loss for Deep Metric Learning | – | 2 |
| ZLPR Loss Zero-bounded Log-sum-exp & Pairwise Rank-based Loss | – | 2 |
| DHEL Decoupled Hyperspherical Energy Loss | – | 1 |
| DSAM loss Distance Shrinking with Angular Marginalizing Loss | – | 1 |
| Dual Softmax Loss | – | 1 |
| GHM-C Gradient Harmonizing Mechanism C | – | 1 |
| GHM-R Gradient Harmonizing Mechanism R | – | 1 |
| HBM Loss Hierarchy-aware Biased Bound Margin Loss | – | 1 |
| Metrix Metric mixup | – | 1 |
| OA-Loss Object-Aware Loss | – | 1 |
| PIoU Loss | – | 1 |
| Self-Adjusting Smooth L1 Loss | – | 1 |
| Triplet Entropy Loss | – | 1 |
| UFLoss Unsupervised Feature Loss | – | 1 |