4 papers
GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries
Ruiling Jiang, Yong Zhang, Houbiao Li
Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent challenges in maintaining physic…
FlatFormer: A Flat Transformer Knowledge Tracing Model Based on Cognitive Bias Injection
Xiao-li Xia, Hou-biao Li
Knowledge Tracing (KT) models face a critical ``Performance-Complexity Trap'': capturing complex cognitive dynamics like learning sessions and memory decay typically requires deep…
U-WNO: U-Net Enhanced Wavelet Neural Operator for Solving Parametric Partial Differential Equations
Wei-Min Lei, Hou-Biao Li
High-frequency features are critical in multiscale phenomena such as turbulent flows and phase transitions, since they encode essential physical information. The recently proposed…
MgFNO: Multi-grid Architecture Fourier Neural Operator for Parametric Partial Differential Equations
Zi-Hao Guo, Hou-Biao Li
Neural operators are a new type of models that can map between function spaces, allowing trained models to emulate the solution operators of partial differential equations (PDEs).…