Gated Recurrent Unit (GRU)

URI: https://gptkb.org/entity/Gated_Recurrent_Unit_%28GRU%29
GPTKB entity
Statements (59)
Predicate Object
gptkbp:instance_of gptkb:microprocessor
gptkbp:bfsLayer 3
gptkbp:bfsParent gptkb:microprocessor
gptkbp:benefits LSTM in training speed
gptkbp:developed_by gptkb:Yoshua_Bengio
gptkbp:has reset gate
update gate
gptkbp:has_method hidden state
input vector
output vector
gptkbp:has_weakness LSTM in performance on complex tasks
https://www.w3.org/2000/01/rdf-schema#label Gated Recurrent Unit (GRU)
gptkbp:introduced gptkb:2014
gptkbp:is_compared_to gptkb:Long_Short-Term_Memory_(LSTM)
gptkbp:is_evaluated_by F1 score
accuracy
loss function
gptkbp:is_implemented_in gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
gptkbp:is_part_of gptkb:microprocessor
gptkb:Deep_Learning
gptkbp:is_similar_to gptkb:LSTM
gptkbp:is_used_for sequence prediction
gptkbp:is_used_in gptkb:robot
language translation
computer vision
financial forecasting
image recognition
natural language processing
reinforcement learning
signal processing
speech recognition
sentiment analysis
chatbots
weather prediction
data compression
fraud detection
recommendation systems
video analysis
time series forecasting
feature extraction
healthcare analytics
text generation
anomaly detection
image generation
text summarization
social media analysis
text classification
optical character recognition
network traffic analysis
image captioning
music generation
video classification
customer behavior prediction
biomedical signal analysis
game AI
gptkbp:requires large datasets
gptkbp:suitable_for vanilla RNN
gptkbp:training backpropagation through time