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Introduction to Image Generation: Quiz

1. What is the process of forward diffusion?

A. Start with a clean image and add noise iteratively

B. Start with a noisy image and remove noise randomly

C. Start with a noisy image and remove noise iteratively

D. Start with a clean image and add noise randomly

2. What is the name of the model family that draws inspiration from physics and thermodynamics?

A. Diffusion models

B. Autoregressive models

C. Variational autoencoders

D. Generative adversarial networks

3. What is the goal of diffusion models?

A. To learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space

B. To encode images to a compressed size, then decode back to the original size

C. To pit two neural networks against each other

D. To generate images by treating an image as a sequence of vectors

4. Which process involves a model learning to remove noise from images?

A. Forward diffusion

B. Reverse diffusion

C. Sampling

D. GANs

5. What are some challenges of diffusion models?

A. They can be computationally expensive to train.

B. All of the above

C. They can be difficult to control.

D. They can generate images that are not realistic.

Answers:

1: A, 2: A, 3: A,4: B,5:B