Abstract: Several merged sea surface temperature (SST) datasets have been produced using different analysis schemes. In high-resolution SST analysis—whether based on optimal interpolation (OI) or ...
ABSTRACT: The alternating direction method of multipliers (ADMM) and its symmetric version are efficient for minimizing two-block separable problems with linear constraints. However, both ADMM and ...
New funding to fuel market expansion of compute efficient foundation model for biopharmaceutical companies VANCOUVER, British Columbia--(BUSINESS WIRE)--#deepseek--Variational AI, the company behind ...
Abstract: Variational autoencoders (VAEs) have emerged as powerful tools for data compression and representation learning. In this study, we explore the application of VAE-based neural compression ...
This repository contains the official PyTorch implementation of the Conference on Information and Knowledge Management (CIKM) 2025 paper: "Causal Effect Variational Transformer for Public Health ...
This project provides a comprehensive analysis of Variational Autoencoders (VAE) and traditional Autoencoders (AE) for image compression tasks. The analysis focuses on the impact of various model ...
Rockafellar, R. and Wets, R. (2009) Variational Analysis. Springer Science & Business Media, Berlin.
ABSTRACT: In this paper, we modify the Bregman APGs (BAPGs) method proposed in (Wang, L, et al.) for solving the support vector machine problem with truncated loss (HTPSVM) given in (Zhu, W, et al.), ...
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