Uses of Class
org.deeplearning4j.nn.conf.layers.FeedForwardLayer

Packages that use FeedForwardLayer

Package	Description
org.deeplearning4j.nn.conf.layers

Uses of FeedForwardLayer in org.deeplearning4j.nn.conf.layers

Subclasses of FeedForwardLayer in org.deeplearning4j.nn.conf.layers

Modifier and Type	Class and Description
class	ActivationLayer
class	AutoEncoder Autoencoder.
class	BaseOutputLayer
class	BasePretrainNetwork
class	BaseRecurrentLayer
class	BatchNormalization Batch normalization configuration
class	ConvolutionLayer
class	DenseLayer Dense layer: fully connected feed forward layer trainable by backprop.
class	EmbeddingLayer Embedding layer: feed-forward layer that expects single integers per example as input (class numbers, in range 0 to numClass-1) as input.
class	GravesBidirectionalLSTM LSTM recurrent net, based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks http://www.cs.toronto.edu/~graves/phd.pdf
class	GravesLSTM LSTM recurrent net, based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks http://www.cs.toronto.edu/~graves/phd.pdf
class	OutputLayer Output layer with different objective co-occurrences for different objectives.
class	RBM Restricted Boltzmann Machine.
class	RnnOutputLayer