4 papers
LGFNet: Local-Global Fusion Network with Fidelity Gap Delta Learning for Multi-Source Aerodynamics
Qinye Zhu, Yu Xiang, Jun Zhang +1
The precise fusion of computational fluid dynamic (CFD) data, wind tunnel tests data, and flight tests data in aerodynamic area is essential for obtaining comprehensive knowledge o…
IIKL: Isometric Immersion Kernel Learning with Riemannian Manifold for Geometric Preservation
Zihao Chen, Wenyong Wang, Jiachen Yang +1
Geometric representation learning in preserving the intrinsic geometric and topological properties for discrete non-Euclidean data is crucial in scientific applications. Previous r…
Disentangling Granularity: An Implicit Inductive Bias in Factorized VAEs
Zihao Chen, Yu Xiang, Wenyong Wang
Despite the success in learning semantically meaningful, unsupervised disentangled representations, variational autoencoders (VAEs) and their variants face a fundamental theoretica…
Learning with Geometry: Including Riemannian Geometric Features in Coefficient of Pressure Prediction on Aircraft Wings
Liwei Hu, Wenyong Wang, Yu Xiang +1
We propose to incorporate Riemannian geometric features from the geometry of aircraft wing surfaces in the prediction of coefficient of pressure (CP) on the aircraft wing. Contrary…