APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
Mode collapse is when ____
|
|
The Generator learns a parameter setting where it only produces one or a select few points.
|
|
|
The Generator cannot learn as the Discriminator classifies all the Generator’s samples as fake thereby producing a useless learning signal.
|
|
|
The Generator is too deep and suffers from vanishing gradients.
|
|
|
None of the above
|
Explanation:
Detailed explanation-1: -Mode collapse is when the GAN produces a small variety of images with many duplicates (modes). This happens when the generator is unable to learn a rich feature representation because it learns to associate similar outputs to multiple different inputs. To check for mode collapse, inspect the generated images.
Detailed explanation-2: -When discriminator gets stuck in a local minimum, the generator exploits this by finding a very plausible set of outputs and keeps repeating them over and over. This form of GAN failure is called mode collapse.
Detailed explanation-3: -Unrolled GAN lowers the chance that the generator is overfitted for a specific discriminator. This lessens mode collapse and improves stability.
There is 1 question to complete.