While many nonlinear pattern recognition and data mining tasks rely on embedding the data into a latent space, one often needs to extract the patterns in the input space. Estimating the inverse of the nonlinear embedding is the so-called pre-image problem. Several strategies have been proposed to ad...

Diffusion models benefit from instillation of task-specific information into the score function to steer the sample generation towards desired properties. Such information is coined as guidance. For example, in text-to-image synthesis, text input is encoded as guidance to generate semantically align...

This paper presents a review and discussion of the concept and measurement of destination image, within an intradisciplinary marketing perspective. Both theoretical and methodological aspects of this concept and measurement are treated. Based on the existence of three dimensions of object, subject a...

Generative Adversarial Networks (GANs) have been successful in producing outstanding results in areas as diverse as image, video, and text generation. Building on these successes, a large number of empirical studies have validated the benefits of the cousin approach called Wasserstein GANs (WGANs), ...

Recent research has demonstrated that neural and behavioral data acquired in response to viewing face images can be used to reconstruct the images themselves. However, the theoretical implications, promises, and challenges of this direction of research remain unclear. We evaluate the potential of th...