# Tag Info

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 ...
• 3,083

### How can we find find the input image which maximizes the class-probability for an ANN?

Probably the simplest way to search for an image with the highest probability of being a cat is to use a technique similar to Deep Dream: Load the network for training, but freeze all the network ...
• 23.2k
Accepted

• 8,865
Accepted

### How can AI be used to more reliably analyze and plan around the tie between climate and emissions?

Can AI provide a more reliable analysis of the gross effects of carbon emissions on extinctions of species ice-cap melting, and other effects? Yes. The work of Judea Pearl and others over the last 20 ...
• 8,865
Accepted

### What are the possible social consequences of training neural networks with artificially generated data?

We can already observe information bubbles on social media, where the circle is that the ML algorithms learn what content people like and give more similar content based on clicks and so on. From a ...
• 927
Accepted

### Query regarding the minmax loss function formulation of the training of a Generative Adversarial Network (GAN)

I'll answer your questions one by one: In this equation are the $E_{z \sim p_z(z)}$ and $E_{x \sim p_{data}(x)}$ the means of the distributions of the mini batch samples? So let's take the first ...
• 3,083

### What parameters can be tweaked to avoid a generator or discriminator loss collapsing to zero when training a DC-GAN?

GANs are notably hard to train and it is not uncommon to have large bumps in the losses. The learning rate is a good start but the instability may come from a wide variety of reasons. I'm assuming ...
• 246

• 746
1 vote
Accepted

### What is the purpose of the noise injection in the generator network of a GAN?

Your goal is to model a distribution when constructing a GAN, therefore you need a way to be able to sample that distribution. The noise's purpose is so you can do this. Generally, it's drawn from a ...
• 2,229
1 vote

### Which libraries can be used for image caption generation?

Image Caption Generation is an interesting problem to work on. I think your question was to know if there are any open-source libraries with built-in functions for Image Captioning. You can build ...
1 vote

### How important is it that the generator of a generative adversarial network doesn't take in information about input classes?

If you're building a straight "vanilla" generative adversarial network, it's best to understand the network as a statistical engine: You are training the generator on samples of a statistical ...
• 161
1 vote
Accepted

### How to get good results with GAN and some thousands of images?

With a Google Cloud V100 GPU the GAN would run a week to two with default parameters. Does this sound realistic time for this kind of dataset? It's definitely not feasible for me. Yes, V100s are ...
• 1,145

Only top scored, non community-wiki answers of a minimum length are eligible