Questions tagged [generative-adversarial-networks]

For questions related to generative adversarial networks (GANs), introduced in the paper Generative Adversarial Nets (2014) by J. Goodfellow et al. A GAN is composed of a discriminative model (D) and a generative model (G). The discriminator D needs to distinguish between data generated by the generator G and data in the training set, while the generator G needs to generate data such that the discriminator D is not able to accomplish its task.

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22 views

What is the best way to generate handwritten text documents?

I am new to generative models. I was wondering if it would be better to generate an image of a handwritten text document as a whole (which I don't know how exactly is done), or first generate ...
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31 views

Is a Conv2DTranspose the same as a full convolution?

I am currently creating a GAN model from scratch (following this tutorial: https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-an-mnist-handwritten-digits-from-...
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Adversarial Autoencoder is not working and not learning properly

I am trying to get an Adversarial AutoEncoder going using keras Fit method on a keras.model class but for some reason it is not working. Keep in mind that I tried updating encoder and decoder at the ...
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Improve generalization of phishing website detection with computer vision

I want to use computer vision to detect phishing websites. There has already been some study on this, which showed this is effective. Most phishing sites try to replicate well-known websites such as ...
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2answers
60 views

Validation set performance increasing even after seemingly overfit on training set

I am training a semi-supervised GAN network using data from multiple subjects. I separated the labeled and unlabeled data based on my subjects, so there is no leakage, while having much more unlabeled ...
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51 views

Discrepencies between the TimeGan paper and the code?

I recently read the paper Time-Series Generative Neural Networks and found the results that they reported quite promising (https://proceedings.neurips.cc/paper/2019/file/...
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19 views

How to understand the results of a generator that switches, for metric evaluation?

I am running a code on generative adversarial networks. The code is designed in such a way that it outputs a fake image after every 5 epochs. The total number of epochs is 800 in number. After the ...
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20 views

How to assess the goodness of a text generation algorithm

Take a RNN network fed with Shakespeare and generating Shakespeare-like text. Once a model seems mathematically fine, as can be assessed by observing its loss and accuracy over training epochs, how ...
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45 views

What is the confusion loss for adversarial learning?

What is the confusion loss used in domain adaptation (DA) for adversarial learning/GANs? See this paper. Two domains: $s$: source domain $t$: target domain Generator/Discriminator setting: $M_s:x_s\...
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31 views

Is it impossible to evaluate the generator distribution directly?

The following excerpt is taken from 3. The Inception Score for Image Generation from the paper titled A Note on the Inception Score. Suppose we are trying to ...
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What is meant by inverting the generator?

Generative Adversarial Networks, in general, consists of two multi layer perceptrons: generator and discriminator. Generator is used for generating samples that are as real as training samples and ...
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22 views

How did authors ensure that critical points do exist in GAN?

Using an MLP as a generator introduces multiple critical points in parameter space. You can read this excerpt from the research paper titled Generative Adversarial Nets by Ian J. Goodfellow et al. In ...
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31 views

When can we call a loss function "adaptive"?

A loss function is a measure of how bad our neural network is. We can decrease the loss by proper training. I came across the phrase "adaptive loss function" in several research papers. For ...
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Is the following a typo or am I understanding wrongly regarding discriminator?

Consider the following paragraph from the section 3: Background of the research paper titled Generative Adversarial Text to Image Synthesis by Scott Reed et al. ...
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Expression Transfer Deep Learning Problem

I have old video and I want to keep the person's face in the video but I want to transfer my facial expressions to that video. Is there any better alternative to first order motion model for that task ...
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What is currently the best GAN architecture for style transfer?

I know that StyleGan is producing great results. But I am not sure if it can be used for Style Transfer. My task is applying style from a real dataset A into a synthetic dataset B.
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1answer
92 views

Is discriminator a regressor or classifier in implementations?

GAN has two components: generator and discriminator. Discriminator in the original GAN is a regressor and always gives value in $[0, 1]$. You can read it in original paper $D(x)$ represents the ...
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1answer
26 views

How can GPT-3 be used for designing electronic circuits from text descriptions?

I was wondering if it is possible to use GPT-3 to translate text description of a circuit to any circuit design language program, which in turn can be used to make the circuit. If it is possible, what ...
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36 views

Can NeuralHash be used as a loss for an Autoencoder?

I've recently read about NeuralHash, and immediately thought that it might be used as a loss for an autoencoder. However, it only seems to preserve "structure" from what I've read, not ...
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What is meant by non-convergent limit cycles?

Limit cycle is a closed curve that is isolated i.e., no other closed curve near to it. You can read the following paragraph from here If there is (such) a closed curve, the nearby trajectories must ...
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Do I need to imagine loss curves of changing shapes in case of GANs?

Loss function, in general, is imagined as a curve in higher dimensional space with weights on input axes and loss on output axes. Suppose we have a neural network and we are training our neural ...
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1answer
42 views

Is image generation not existent before generative adversarial networks?

Although the GAN is widely used due to its capability, there were generative models before the GAN which are based on probabilistic graphical models such as Bayesian networks, Markov networks, etc. It ...
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1answer
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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 ...
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32 views

Is there any difference between input and conditional input incase of neural networks?

In the research paper titled Conditional Generative Adversarial Nets by Mehdi Mirza and Simon Osindero, there is a notion of conditioning a neural network on class label. It has been mentioned in <...
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49 views

Does generator in conditonal GAN obey probability laws?

In probability, we have two types of probability functions: unconditional probability $p(x)$ and conditional probability $p(x | y)$. Both are fundamentally different and the latter can be obtained by ...
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How accurate is this table from the original GAN paper summarizing difficulties and properties for deep generative models?

In the original GAN paper, they talk about how inference and training might be done in other deep generative models. In no particular order I was confused by: what is meant by "Learned ...
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What does it mean by strong or sufficient gradient for training in this context?

It has been mentioned in the research paper titled Generative Adversarial Nets that generator need to maximize the function $\log D(G(z))$ instead of minimizing $\log(1 −D(G(z)))$ since the former ...
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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 ...
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Why is the proof of convergence in the GAN paper not applicable practically?

This question is about generative adversarial networks and restricted to the research paper titled Generative Adversarial Nets. If I select a particular architecture of MLP as a generator and trained ...
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23 views

How to handle critical points during generator training?

Using an MLP as a generator introduces multiple critical points in parameter space. You can read this excerpt from the research paper titled Generative Adversarial Nets by Ian J. Goodfellow et al. In ...
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1answer
38 views

What are the iid random variables for a dataset in the GAN framework?

I am trying to understand why mean is used for expectation in training Generative Adversarial Networks. The answer tells that it is due to the law of large numbers which is based on the assumption ...
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31 views

Are there any Generative Adversarial Networks without Multi Layer Perceptrons?

Although the main stream research is on Generative Adversarial Networks(GANs) using Multi Layer Percepteons (MLPs). The original paper titled Generative Adversarial Nets clealry says, in abstract, ...
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Which probability distribution a generator in Generative Adversarial Network (GAN) is capturing: dataset or ground truth?

Consider the following statement from the abstract of the paper titled Generative Adversarial Nets We propose a new framework for estimating generative models via an adversarial process, in which we ...
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2answers
278 views

What is Lipschitz constraint and why it is enforced on discriminator?

The following is the abstract for the research paper titled Improved Training of Wasserstein GANs Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training ...
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GAN performs worse after 50 epochs than after 2

I am training GAN on SVHN dataset (house numbers in Google Street View images, dimensions: 3x32x32 - 3 color channels). The problem is that it performs worse after some training (e.g. after 50 epochs) ...
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What is the state of the art in melody generation?

Generative Adversarial Networks can generate realistic photos of people, such as thispersondoesnotexist.com. I wonder whether one can train an artificial intelligence on a batch of plain solo melodies ...
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81 views

Is it possible to mimic someone's handwriting given their sample notes?

I have a pet project, but I'm not very well versed with AI. I posted this question on datascience.stackexchange with no luck. I think this forum is more apt, so can anyone here help me start this in ...
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Using GAN to create multiple images as per multiple input layers

How to use GAN to create multiple images like https://opensea.io/collection/boredapeyachtclub here, each attribute is variable like fur, BG, Expression, Sunglasses, etc. Is there any GAN software to ...
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GAN - relation of input size and hidden layer size

I'm adapting a GAN described here used for generating binary output. It's trained on binarized MNIST data, with a size of 28x28 so 784 values. I want to adapt it to train on and generate 1D vectors ...
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22 views

Text to image GANs and failure

My knowledge of GANs is relatively basic at the moment but I seem to remember reading somewhere that GANs that generate images from a text prompt, when they fail to understand some of the text/words ...
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64 views

Is there a performace benefits using VAE-GAN instead of just GAN?

I have read that when using VAE-GANs, first what happens is the VAE's encoder encodes some image to another encoded image, which from GAN's point of view is considered a noise, and then the GAN part ...
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GAN unexpected behavior depeding on scaling and generator output activation function

I am training a GAN using data that underwent PCA. When I scale the data between -1 and 1, no matter when I use 'tanh' or 'sigmoid' at the last layer of the generator, the network is not stable. ...
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Hyperparameters for Reproducing the Results of IRGAN on MovieLens 1M

I am trying to reproduce results reported for IRGAN (information retrieval GAN) on the MovieLens 1M dataset. The results I want to reproduce and their sources are listed in the table below. Model ...
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1answer
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In style transfer, why does the comparison between channels give a good sense of style?

I have been learning about Style Transfer recently. Style is defined as The correlation of activations between channels. I can't seem to understand why that would be true. Intuitively, style seems ...
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Are generative models actually used in practice for industrial drug design?

I just finished reading this paper MoFlow: An Invertible Flow Model for Generating Molecular Graphs. The paper, which is about generating molecular graphs with certain chemical properties improved the ...
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Things to consider while adding custom function to generator output in GAN

I am training a GAN model (DCGAN) to generate 128x128 images. Now, I wish to add a function which will take the generator output, perform some pre-defined operations on it, and return the modified ...
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Which approach best suits vector encodings?

I want to build a model that when given two vectors, outputs the probability of one vector being the encoded form of the other. I have 2 strategies for this: (Dataset available) I can directly feed ...
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1answer
35 views

Are there architectures to generate pictures from four labels? (VAEs, GANs)

I want to try something with image creation via NNs. I have come across Variational Autoencoders and Generative Adversarial Networks as possible solutions but have only found image creatinon with ...
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1answer
66 views

Decision boundary figure in Least square GAN paper

I currently reading Least Square GAN paper. But, I cannot interpret the one of the its figures. . Explanation of the figure goes like this: Figure 1: Illustration of different behaviors of two loss ...
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Is it possible to use an internal layer's outputs in a loss function?

For a network of the form: Input(10) Dense(200) Dense(100+10) Dense(20) Output() Those +10 outputs are what I want to add to ...