3 papers
math.NA2026
Parametric Probabilistic Manifold Decomposition for Nonlinear Model Reduction
Jiaming Guo, Dunhui Xiao
Probabilistic Manifold Decomposition (PMD)\cite{doi:10.1137/25M1738863}, developed in our earlier work, provides a nonlinear model reduction by embedding high-dimensional dynamics…
cs.SE2025
QiMeng-MuPa: Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
Changxin Ke, Rui Zhang, Shuo Wang +11
The rise of GPU-based high-performance computing (HPC) has driven the widespread adoption of parallel programming models such as CUDA. Yet, the inherent complexity of parallel prog…
math.NA2025
Nonlinear Model Reduction by Probabilistic Manifold Decomposition
Jiaming Guo, Dunhui Xiao
This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduce…