A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

Jianwei Shuai's team and Jiahuai Han's team at Xiamen University have developed a deep autoencoder-based data-independent acquisition data analysis software for protein mass spectrometry, which ...

Qamrul Hasan Ansari *, Somayeh Eshghinezhad, Majid Fakhar, EKELAND'S VARIATIONAL PRINCIPLE FOR SET-VALUED MAP SWITH APPLICATIONS TO VECTOR OPTIMIZATION IN UNIFORM SPACES, Taiwanese Journal of ...

This led us to analyze online variational learning approach for finite mixture models based on different distributions. To this end, our contribution is the application of online variational learning ...

In this paper, we introduce two inertial self-adaptive projection and contraction methods for solving the pseudomonotone variational inequality problem with a Lipschitz-continuous mapping in real ...

However, each of these choices has its own limitations. In this thesis, these limitations are discussed and addressed via defining a variational inference framework for finite inverted Dirichlet ...