Beyond its methodological contribution, the study offers new insights into how stimulus-driven variability and internally generated gain fluctuations evolve over time and between brain areas. The ...

Abstract: The paper proposes a new Kalman filtering (KF) algorithm called VBI-MCKF that combines the variational Bayesian inference (VBI)-based KF algorithm and the maximum correntropy KF (MCKF) for ...

Variational quantum algorithms, which use a classical computer to optimize parameters of a quantum circuit, have emerged as a promising solution for near-term quantum computing due to their inherent ...

Variational quantum algorithms are a class of techniques that are particularly suitable for near-term applications and borrow many ideas from classical variational methods in quantum chemistry and ...

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.

Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, People’s Republic of China ...

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices ...

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...