Quantum Machine Learning - An Introduction to QGANs - insideBIGDATA

Since Alex Krizhevsky's breakthrough in imagenet competition, deep learning has been transforming the way we process large scale complex data with computers. Deep neural networks can perform image and speech recognition at very high accuracies. One of the exciting developments in deep learning is generative adversarial networks- GANs which have many applications: image generation, generation of 3d objects, text generation, generation of synthetic data for chemistry, biology and physics. Quantum GANs which use a quantum generator or discriminator or both is an algorithm of similar architecture developed to run on Quantum systems. The quantum advantage of various algorithms is impeded by the assumption that data can be loaded to quantum states.