Generative Adversarial Networks
David Paper
Abstract
Generative modeling is an unsupervised learning technique that involves automatically discovering and learning the regularities (or patterns) in input data so that a trained model can generate new examples that plausibly could have been drawn from the original dataset. A popular type of generative model is a generative adversarial network. Generative adversarial networks (GANs) are generative models that create new data instances that resemble the training data.
Topics & Concepts
Generative grammarAdversarial systemComputer scienceArtificial intelligenceGenerative adversarial networkGenerative modelMachine learningDeep learningImage Processing and 3D ReconstructionGenerative Adversarial Networks and Image SynthesisComputational Physics and Python Applications