Tag Info

Accepted

Is the new AlphaGo implementation using Generative Adversarial Networks?

No, GANs are not used. It's reinforcement learning at what it does best. The tree search is an interesting addition and assists with navigating the sheer scale of the game. Although the agent was ...
• 3,587
Accepted

What is the meaning of $V(D,G)$ in the GAN objective function?

To understand this equation first you need to understand the context in which it is first introduced. We have two neural networks (i.e. $D$ and $G$) that are playing a minimax game. This means that ...
• 3,093

If you start with perpect discriminator, loss function will be saturated, and gradient of loss will be very small, so feedback for the generator also will be small, and learning will be slow down as a ...
• 174

Why is it called Latent Vector?

Latent is a synonym for hidden. Why is it called a hidden (or latent) variable? For example, suppose that you observe the behaviour of a person or animal. You can only observe the behaviour. You ...
• 33.8k
Accepted

Can someone explain R1 regularization function in simple terms?

Here is how I understand this regularization. $R_1$ is simply the norm of the gradients, which indicates how fast the weights will be updated. Gradient regularization penalizes large changes in the ...
• 742

How are generative adversarial networks trained?

Compare generated and real data All the results produced by G are always considered "wrong" by definition, even for a very good generator. You provide the discriminative neural network $D$ with a ...
• 853

Why is the variational auto-encoder's output blurred, while GANs output is crisp and has sharp edges?

The key is: VAE usually use a small latent dimension, the information of input is so hard to pass through this bottleneck, meanwhile it tries to minimize the loss with the batch of input data, you ...
• 49
Accepted

Isn't deep fake detection bound to fail?

Not necessarily it depends on the function of the problem space for both the GANs. A real world example: a batter's reaction time and a pitchers max speed are actual bounded values based on genetics ...
Accepted

• 742
Accepted

Why are GAN models not heavily used for NLP?

A couple of reasons: Transformers are amazing at text generation already (e.g. GPT-3 which almost passes the Turing-Test) The original GAN requires a continuous data representation (e.g. images) ...
• 276