Description: Latent Dynamics refers to the study of how latent variables, which are not directly observable but influence observable data, evolve over time in generative models. These dynamics are fundamental to understanding the complexity of the systems to which they are applied, as they allow for modeling and predicting underlying behaviors in various fields such as economics, biology, and artificial intelligence. In the context of generative models, Latent Dynamics are used to capture the evolution of generative features as models are trained. This implies that latent variables can be manipulated to generate different outputs, providing significant control over the generation process. The ability to model these dynamics enables researchers and developers to explore new ways of content creation, model optimization, and data analysis, thus facilitating innovation in the field of artificial intelligence and machine learning.
