GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
Frontiers

A hierarchical Bayesian inference model for volatile multivariate exponentially distributed signals

Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The ...
C&EN

MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data

State Key Laboratory of Medical Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China University of Chinese Academy of Sciences, Beijing 100049, P.
IEEE

Latent Space Bayesian Parameter Topology Optimization of Permanent Magnet Synchronous Motors via a Variational Autoencoder

Abstract: This study introduces a novel approach that combines a variational autoencoder and Bayesian optimization to accelerate the simultaneous parameter and topology optimization of interior ...
Frontiers

An islanding detection method for grid-connect inverter based on parameter optimized variational mode decomposition and deep learning

The rapid and effective islanding detection and disconnection of the microgrid are significant for preventing equipment from failure and safeguarding humanity’s safety. To address the drawbacks of ...
Scientific Research Publishing

Gabay, D. (1983) Applications of the Method of Multipliers to Variational Inequalities. In: Studies in Mathematics and Its Applications, Elsevier, 299-331.

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.