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Generative Models for Image Synthesis

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Questions and Answers

What is the primary goal of the generator in a GAN?

To update the parameters of the discriminator

To classify the input data as real or fake

To distinguish between real and fake samples

To create samples that are as realistic as possible to fool the discriminator (correct)

What is the condition under which the training of a GAN is stopped?

When the generator is unable to generate new samples

When the discriminator is able to distinguish between fake and real samples with 100% accuracy

When the generator is able to fool the discriminator

When the discriminator is unable to distinguish between fake and real samples (correct)

What is the output of the discriminator in a GAN?

A probabilistic value in the interval (0,1) (correct)

A continuous value indicating the degree of realism

A binary label indicating real or fake

A categorical label indicating real or fake

What is the typical application domain of GANs?

Image Domain Signup and view all the answers

What is the type of learning paradigm used in GANs?

Unsupervised Learning Signup and view all the answers

What is the role of the random noise Z in GANs?

To provide a probabilistic input to the generator Signup and view all the answers

What is the goal of the Discriminator?

To maximize its reward Signup and view all the answers

What is the purpose of the Generator in the GAN framework?

To generate synthetic examples Signup and view all the answers

What is the role of stochastic gradient ascent in the GAN framework?

To update the Discriminator's parameters Signup and view all the answers

How many times is the Discriminator updated for each update of the Generator?

k times Signup and view all the answers

What is the purpose of repeating the construction of mini-batches?

To train the Discriminator Signup and view all the answers

What is the input to the Generator to create synthetic examples?

Noise samples from the prior distribution Signup and view all the answers

What is one of the primary applications of generated objects in machine learning?

Data augmentation Signup and view all the answers

What is the primary distinction between generative and discriminative models?

Ability to generate new images Signup and view all the answers

What is the term used to describe the optimization problem between the generative and discriminative models?

Minimax game Signup and view all the answers

What is the conditional probability estimated by discriminative models?

P(y|X) Signup and view all the answers

What type of learning approach can generative models be used in?

Both supervised and unsupervised learning Signup and view all the answers

What is an example of a context that can be added to generate objects with different properties?

Text caption Signup and view all the answers