Variational Bayesian MultimodalEncephaloGraphy (VBMEG): Its Theory and Applications

FUZZY SOFT SET THEORY AND ITS APPLICATIONS

In this work, we define a fuzzy soft set theory and its related properties. We then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. Finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

fuzzy soft set theory and its applications

in this work, we define a fuzzy soft set theory and its related properties. we then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

Stein Variational Gradient Descent: Theory and Applications

Although optimization can be done very efficiently using gradient-based optimization these days, Bayesian inference or probabilistic sampling has been considered to be much more difficult. Stein variational gradient descent (SVGD) is a new particle-based inference method derived using a functional gradient descent for minimizing KL divergence without explicit parametric assumptions. SVGD can be...

Theory and Applications of Variational Inequalities

Large Scale Variational Bayesian Inference and its Application to MRI

Reducing scan times in MRI is a major concern due to its inherently slow acquisition process. Fortunately, the properties of MRI make it a good target for ideas from compressed sensing which provides a theory for recovering sparse signals from a small, random subset of the measurements required for linear reconstruction. A Bayesian method is presented to improve upon the non-adaptive measuremen...