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gptkbp:instanceOf
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Machine Learning Model
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gptkbp:application
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gptkb:Speech_Synthesis
Data Augmentation
Text Generation
Anomaly Detection
Drug Discovery
Image Generation
Molecule Generation
|
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gptkbp:canBe
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Unsupervised
Supervised
Semi-supervised
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gptkbp:challenge
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Evaluation Metrics
Mode Collapse
Training Instability
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gptkbp:example
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gptkb:Variational_Autoencoder
gptkb:convolutional_neural_network
Autoregressive Model
Normalizing Flow
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gptkbp:field
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gptkb:Machine_Learning
gptkb:artificial_intelligence
Deep Learning
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https://www.w3.org/2000/01/rdf-schema#label
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Deep Generative Model
|
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gptkbp:learns
|
Data Distribution
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gptkbp:notableContributor
|
gptkb:Ian_Goodfellow
gptkb:Yoshua_Bengio
gptkb:Diederik_P._Kingma
gptkb:Max_Welling
|
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gptkbp:notablePublication
|
gptkb:Generative_Adversarial_Nets_(2014)
Auto-Encoding Variational Bayes (2013)
Pixel Recurrent Neural Networks (2016)
Real NVP (2016)
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gptkbp:output
|
Sample
Probability Distribution
Synthetic Data
|
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gptkbp:popularizedBy
|
2010s
|
|
gptkbp:purpose
|
gptkb:Unsupervised_Learning
Density Estimation
Data Generation
|
|
gptkbp:relatedTo
|
gptkb:Representation_Learning
gptkb:Latent_Variable_Model
Bayesian Inference
Probabilistic Model
|
|
gptkbp:trainer
|
gptkb:Reinforcement_Learning
gptkb:Variational_Inference
Maximum Likelihood Estimation
Adversarial Training
|
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gptkbp:uses
|
gptkb:Neural_Network
gptkb:Deep_Neural_Network
Stochastic Process
Optimization Algorithm
|
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gptkbp:bfsParent
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gptkb:Deep_Boltzmann_Machines
|
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gptkbp:bfsLayer
|
8
|