Abstract: Methods based on variational bayes theorytare widely used to detect community structures in networks. In recent years, many related methods have emerged that provide valuable insights into ...

Ever opened a file and seen strange symbols or jumbled text? That’s usually an encoding problem; your software isn’t reading the data correctly. The good news is that Microsoft Office makes it easy to ...

The rapid growth of large-scale neuroscience datasets has spurred diverse modeling strategies, ranging from mechanistic models grounded in biophysics, to phenomenological descriptions of neural ...

ABSTRACT: Large models perform better than traditional deep learning methods in terms of generalization and continuous learning capabilities, but the application of large models in vertical fields ...

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...

Introduction 论文的 introduction 部分我们略过，直接看 method 部分。 2. Method 本节中的策略可用于为具有连续潜在变量(隐变量 ...

Electromagnetic brain imaging is the reconstruction of brain activity from non-invasive recordings of electroencephalography (EEG), magnetoencephalography (MEG), and also from invasive ones such as ...

Abstract: In this work, we propose a novel variational Bayesian adaptive learning approach for cross-domain knowledge transfer to address acoustic mismatches between training and testing conditions, ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The two terms in this objective formulation achieve dual ...

Parameter shift rules (PSRs) are key techniques for efficient gradient estimation in variational quantum eigensolvers (VQEs). In this paper, we propose its Bayesian variant, where Gaussian processes ...