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Interrupting encoder training in diffusion models enables more efficient generative AI

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...
Visual Studio Magazine

Generating Synthetic Data Using a Variational Autoencoder with PyTorch

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...
JSTOR Daily

EKELAND'S VARIATIONAL PRINCIPLE FOR SET-VALUED MAP SWITH APPLICATIONS TO VECTOR OPTIMIZATION IN UNIFORM SPACES

Abstract In this paper, we introduce the concept of a weak q-distance and for this distance we derive a set-valued version of Ekeland's variational principle in the setting of uniform spaces. By using ...
JSTOR Daily

Application of an Ultra Weak Variational Formulation of Elliptic PDES to the Two-Dimensional Helmholtz Problem

A new technique to solve elliptic linear PDEs, called ultra weak variational formulation (UWVF) in this paper, is introduced in [B. Després, C. R. Acad. Sci. Paris, 318 (1994), pp. 939-944]. This ...