How do you deal with the trade-off between reconstruction and regularization in latent variable models?
Latent variable models are a powerful tool for generative AI, as they can learn to represent complex data distributions and generate new samples. However, they also face a trade-off between reconstruction and regularization, which affects their performance and interpretability. In this article, we will explain what this trade-off is, why it matters, and how to deal with it using different approaches.
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Nebojsha Antic ???? 162x LinkedIn Top Voice | BI Developer - Kin + Carta | ?? Certified Google Professional Cloud Architect and Data…
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Giovanni Sisinna??Portfolio-Program-Project Management, Technological Innovation, Management Consulting, Generative AI, Artificial…
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Vaibhava Lakshmi RavideshikAmbassador @ DeepLearning.AI and @ Women in Data Science Worldwide