| Variant |
Description |
Typical application
|
| Standard dropout |
Drops individual neurons |
Fully connected layers
|
| Spatial dropout |
Drops entire feature maps (channels) |
Convolutional networks
|
| DropConnect |
Drops individual weights instead of neurons |
Dense layers
|
| Variational dropout |
Learns the dropout rate per neuron/weight |
bayesian deep learning
|
| DropBlock |
Drops contiguous regions of feature maps |
Convolutional networks
|
| Alpha dropout |
Maintains self-normalizing property (for SELU activations) |
Self-normalizing networks
|
