35 citations · 58 across the 8 of their papers we have counts for
8 papers
PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow
Jiarui Lei, Xiaobo Hu, Yue Wang +1
During industrial processing, unforeseen defects may arise in products due to uncontrollable factors. Although unsupervised methods have been successful in defect localization, the…
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition
Xinquan Huang, Wenlei Shi, Qi Meng +4
Neural networks have shown great potential in accelerating the solution of partial differential equations (PDEs). Recently, there has been a growing interest in introducing physics…
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
Rui Zhang, Qi Meng, Rongchan Zhu +5
In scenarios with limited available data, training the function-to-function neural PDE solver in an unsupervised manner is essential. However, the efficiency and accuracy of existi…
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations
Rui Zhang, Peiyan Hu, Qi Meng +5
Navier-Stokes equations are significant partial differential equations that describe the motion of fluids such as liquids and air. Due to the importance of Navier-Stokes equations,…
VectorMapNet: End-to-end Vectorized HD Map Learning
Yicheng Liu, Tianyuan Yuan, Yue Wang +2
Autonomous driving systems require High-Definition (HD) semantic maps to navigate around urban roads. Existing solutions approach the semantic mapping problem by offline manual ann…
Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs
Peiyan Hu, Qi Meng, Bingguang Chen +6
Stochastic partial differential equations (SPDEs) are significant tools for modeling dynamics in many areas including atmospheric sciences and physics. Neural Operators, generation…