All Questions
6 questions
1
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Is there any difference between an objective function and a value function?
I found the usage of both objective function and value function in the same context.
Context #1: In the paper titled Generative Adversarial Nets by Ian J. Goodfellow et al.
We simultaneously train G ...
- 3,990
0
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1
answer
238
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Does average loss function in GAN training is just an approximation of value function and does not ensure convergence of generator and discriminator?
The value function on which convergence has been proved by the original paper of GAN is
$$\min_G \max_DV(D, G) = \mathbb{E}_{x ∼ P_{data}}[\log D(x)] + \mathbb{E}_{z ∼ p_z}[log (1 - D(G(z)))]$$
and ...
- 3,990
13
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1
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14k
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What are the fundamental differences between VAE and GAN for image generation?
Starting from my own understanding, and scoped to the purpose of image generation, I'm well aware of the major architectural differences:
A GAN's generator samples from a relatively low dimensional ...
- 1,369
1
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0
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134
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What is the difference between using dense layers as opposed to convolutional layers in my networks when dealing with images?
I am thinking about developing a GAN.
What is the difference between using dense layers as opposed to convolutional layers in my networks when dealing with images?
- 11
9
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5
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13k
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Why is the variational auto-encoder's output blurred, while GANs output is crisp and has sharp edges?
I observed in several papers that the variational autoencoder's output is blurred, while GANs output is crisp and has sharp edges.
Can someone please give some intuition why that is the case? I did ...
- 269
7
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1
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7k
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Why doesn't VAE suffer mode collapse?
Mode collapse is a common problem faced by GANs. I am curious why doesn't VAE suffer mode collapse?
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