All Questions
Tagged with neural-networks generative-models
8 questions
22
votes
4
answers
8k
views
Likelihood-free inference - what does it mean?
Recently I have become aware of 'likelihood-free' methods being bandied about in literature. However I am not clear on what it means for an inference or optimization method to be likelihood-free.
In ...
- 967
16
votes
1
answer
18k
views
Variational Autoencoder − Dimension of the latent space
I've done some experiments to understand the influence of the dimension of the latent space in a VAE, and it seems that the higher the space, the harder it is to generate realistic images. I might ...
- 263
13
votes
3
answers
19k
views
Why use Binary Cross Entropy for Generator in Adversarial Networks
I'm trying to work with General Adversarial Networks and there's something I'm seeing everywhere but can't explain why...
the GANs are usually constructed from a Generator (which usually generates an ...
- 515
3
votes
2
answers
897
views
How is the variance for a diffusion kernel derived for a diffusion model?
So I'm watching this video tutorial from CVPR this year on diffusion models, and I am confused by the variance term in the distribution on the left on the video. I understand that in the forward ...
- 31
22
votes
1
answer
6k
views
Why in Variational Auto Encoder (Gaussian variational family) we model $\log\sigma^2$ and not $\sigma^2$ (or $\sigma$) itself?
In theory the encoder in VAE (assuming that variational family is Gaussian) generates the $\mu$ and $\sigma$ (or $\sigma^2$). But, in practice, I have seen people assuming the output is $\log\sigma^2$....
- 1,502
14
votes
3
answers
3k
views
Is the optimization of the Gaussian VAE well-posed?
In a Variational Autoencoder (VAE), given some data $x$ and latent variables $t$ with prior distribution $p(t) = \mathcal{N}(t \mid 0, I)$, the encoder aims to learn a distribution $q_{\phi}(t)$ that ...
- 707
4
votes
1
answer
1k
views
Generative Adversial Networks: how the generator is trained with the output of discriminator
Recently I have learned about Generative Adversarial Networks.
For training the Generator, I am somehow confused how it learns. Here is an implemenation of GANs:
...
- 395
1
vote
0
answers
2k
views
GAN losses balance, but quality of generated image still bad
I build a GAN to train on the fashion mnist dataset.
To facilitate the training, I have added gaussian noise with mean 0 and stddev 0.15 on the images. My generator is a 2 layer MLP with sigmoid ...
- 319