A Bayesian particle Gibbs framework enables unbiased spike time inference with millisecond resolution and jointly estimates uncertainties in both spike timing and model parameters from fast calcium ...
In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...
Exoplanet science has undergone a profound paradigm shift, evolving from its discovery-driven youth into a data-rich and precision-oriented mature era ...
Resources for observational comparative research have expanded enormously in recent years to include very large sources of ...
A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to ...
Abstract: Sparse diagnosis techniques for antenna arrays provide an efficient approach to fault diagnosis by leveraging the sparse nature of faulty elements. In practical scenarios, an unknown ...
CN101 accelerates AI inference, linear algebra, and sampling workloads for diffusion models, a foundational milestone toward dramatically more energy-efficient AI. NEW YORK, Aug. 12, 2025 /PRNewswire/ ...
Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and finite second ...
Abstract: In this work, we have developed a variational Bayesian inference theory of elasticity, which is accomplished by using a mixed Variational Bayesian inference Finite Element Method (VBI-FEM) ...
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