SVGP-KAN is a library for building interpretable, probabilistic, and scalable neural networks. It merges the architecture of Kolmogorov-Arnold Networks (KANs) with the uncertainty quantification of ...
A new AI model called popEVE can predict how likely each variant in a patient’s genome is to cause disease. The team is testing popEVE in clinical settings to see if it can speed accurate diagnoses of ...
The search for gamma-ray counterparts to gravitational-wave events with the CALET Gamma-ray Burst Monitor (CGBM) requires accurate and robust background modeling. Previous CALET observing runs (O3 and ...
ABSTRACT: Aiming at the common issues of poor sound quality and significant artifacts involved in today’s AI singing voice conversion techniques, this paper proposes a new method of AI-driven singing ...
Developing novel materials drives significant breakthroughs across various engineering fields. Recent advancements in computational resources and techniques have enabled comprehensive material ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...
Abstract: This article presents a new Gaussian mixture model-based variational Bayesian approach (VBSDD-ETT) for solving the problem of skew-dense distribution (SDD) of measurement points in the ...
ABSTRACT: Anomaly detection in complex crowd scenes is a challenging task due to the inherent variability in crowd behaviors, interactions, and scales. This paper proposes a novel hybrid model that ...
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