Frontiers

Machine Learning for Inverse Design and Optimization of Metamaterials

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...
JSTOR Daily

Bayesian Variable Selection for High Dimensional Generalized Linear Models: Convergence Rates of the Fitted Densities

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...
JSTOR Daily

Learning from a lot: Empirical Bayes for high-dimensional model-based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
Morningstar

WiMi Lays Out Variational Quantum Algorithms for Multidimensional Data Task Processing

BEIJING, Sept. 12, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced an in ...