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gptkbp:instance_of
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gptkb:Ganon
gptkb:neural_networks
|
|
gptkbp:can_be_combined_with
|
gptkb:stage_adaptation
gptkb:machine_learning
|
|
gptkbp:can_be_used_for
|
gptkb:Speech_Synthesis
Image Generation
Text Generation
|
|
gptkbp:challenges
|
Overfitting
Underfitting
Mode Collapse
|
|
gptkbp:developed_by
|
gptkb:D._P._Kingma
gptkb:M._Welling
|
|
gptkbp:first_introduced
|
gptkb:2013
|
|
gptkbp:has_component
|
Decoder
Encoder
Latent Space
|
|
https://www.w3.org/2000/01/rdf-schema#label
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Variational Autoencoders
|
|
gptkbp:input_output
|
Latent Representation
Reconstructed Data
|
|
gptkbp:is_enhanced_by
|
Regularization Techniques
Advanced Architectures
|
|
gptkbp:is_evaluated_by
|
Real-World Applications
Reconstruction Loss
Benchmark Datasets
KL Divergence
|
|
gptkbp:is_implemented_in
|
gptkb:Tensor_Flow
gptkb:Keras
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
Statistical Learning Theory
Neural Network Advances
Variational Inference Techniques
|
|
gptkbp:is_popular_in
|
gptkb:AI_technology
Machine Learning Community
|
|
gptkbp:is_related_to
|
gptkb:Generative_Adversarial_Networks
Normalizing Flows
|
|
gptkbp:is_trained_in
|
gptkb:Adam_Optimizer
Stochastic Gradient Descent
RMSprop
|
|
gptkbp:is_used_in
|
gptkb:Computer_Vision
gptkb:Natural_Language_Processing
gptkb:robotics
|
|
gptkbp:purpose
|
Anomaly Detection
Dimensionality Reduction
Data Generation
|
|
gptkbp:related_to
|
gptkb:Deep_Learning
Bayesian Inference
Latent Variable Models
|
|
gptkbp:requires
|
Optimization Algorithm
Loss Function
Training Data
|
|
gptkbp:uses
|
Variational Inference
Latent Variables
|
|
gptkbp:bfsParent
|
gptkb:Jürgen_Schmidhuber
|
|
gptkbp:bfsLayer
|
3
|