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gptkbp:instance_of
|
gptkb:neural_networks
|
|
gptkbp:analyzes
|
activation functions
hidden state representations
weight matrices
|
|
gptkbp:can_be_combined_with
|
CNNs
transformers
attention mechanisms
|
|
gptkbp:characteristic
|
gptkb:memory
feedback connections
|
|
gptkbp:developed_by
|
gptkb:Yoshua_Bengio
gptkb:David_Rumelhart
gptkb:Geoffrey_R._Hinton
|
|
gptkbp:has_applications_in
|
language translation
sentiment analysis
chatbots
anomaly detection
stock price prediction
|
|
gptkbp:has_limitations
|
vanishing gradient problem
exploding gradient problem
|
|
gptkbp:has_type
|
gptkb:GRU
gptkb:LSTM
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Recurrent Neural Networks
|
|
gptkbp:is_applied_in
|
speech recognition
video analysis
image captioning
music generation
|
|
gptkbp:is_characterized_by
|
dynamic behavior
temporal dependencies
variable input lengths
|
|
gptkbp:is_evaluated_by
|
gptkb:historical_memory
F1 score
accuracy
precision
loss function
|
|
gptkbp:is_influenced_by
|
regularization techniques
gradient descent
dropout
batch normalization
|
|
gptkbp:is_part_of
|
deep learning
|
|
gptkbp:is_related_to
|
gptkb:Artificial_Intelligence
gptkb:neural_networks
gptkb:machine_learning
|
|
gptkbp:is_trained_in
|
large datasets
time series data
text corpora
audio data
sequential data
|
|
gptkbp:is_used_in
|
gptkb:robotics
healthcare
finance
gaming
social media analysis
|
|
gptkbp:requires
|
backpropagation through time
|
|
gptkbp:training
|
gptkb:Adam_optimizer
stochastic gradient descent
RMSprop
|
|
gptkbp:used_for
|
natural language processing
time series analysis
sequence prediction
|
|
gptkbp:bfsParent
|
gptkb:Hugo_Larochelle
gptkb:API
gptkb:Feedforward_Neural_Network
gptkb:neural_networks
gptkb:Deep_Learning
gptkb:CS224_N:_Natural_Language_Processing_with_Deep_Learning
gptkb:Sepp_Hochreiter
|
|
gptkbp:bfsLayer
|
4
|