How do you prevent mode collapse during the training of GANs especially with imbalanced datasets

0 votes
With the help of python code can you show in the code how to prevent mode collapse during training of GANs?
Nov 7 in Generative AI by Ashutosh
• 3,120 points

edited 6 days ago by Ashutosh 33 views

1 answer to this question.

0 votes

You can prevent mode collapse by the most commonly used technique that is to add a item to the loss function or employ Minibatch Discriminator. Here is the optimized reference below on the usage of Minibatch Discriminator:

In the code above Mini_Batch_Discriminator adds a layer to the discriminator helps in distinguishing between samples with each batch. In this way discriminator learns to detect lack of diversity, reducing model collapse in generator.

answered 6 days ago by viksha mehera

edited 6 days ago by Ashutosh

Related Questions In Generative AI

0 votes
1 answer

How do you reduce mode collapse in GAN training?

A major issue with Generative Adversarial Networks ...READ MORE

answered Nov 5 in Generative AI by rajshri reddy
172 views
0 votes
1 answer
0 votes
1 answer

What are the best practices for fine-tuning a Transformer model with custom data?

Pre-trained models can be leveraged for fine-tuning ...READ MORE

answered Nov 5 in ChatGPT by Somaya agnihotri

edited 6 days ago by Ashutosh 111 views
0 votes
1 answer

What preprocessing steps are critical for improving GAN-generated images?

Proper training data preparation is critical when ...READ MORE

answered Nov 5 in ChatGPT by anil silori

edited 6 days ago by Ashutosh 72 views
0 votes
1 answer

How do you handle bias in generative AI models during training or inference?

You can address biasness in Generative AI ...READ MORE

answered Nov 5 in Generative AI by ashirwad shrivastav

edited 6 days ago by Ashutosh 98 views
webinar REGISTER FOR FREE WEBINAR X
REGISTER NOW
webinar_success Thank you for registering Join Edureka Meetup community for 100+ Free Webinars each month JOIN MEETUP GROUP