collaborators

5 papers

math.NA2026

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…

cs.AI2025

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…

math.NA2025

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…

cs.CV2025

Enhancing Facial Classification and Recognition using 3D Facial Models and Deep Learning

Houting Li, Mengxuan Dong, Lok Ming Lui

Accurate analysis and classification of facial attributes are essential in various applications, from human-computer interaction to security systems. In this work, a novel approach…

math.NA2025

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).…