Definition: MorphGAN is a deep learning architecture designed for generative adversarial networks (GANs) that can generate images similar to those generated by a given input image. It was developed by researchers at Google and Stanford University, under the supervision of Yoshua Bengio. The main idea behind MorphGAN is to use the model's ability to learn from data points to predict new inputs based on their characteristics, such as the shape or color of an object. This allows for a more accurate representation of the
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