1 citations · 2 across the 9 of their papers we have counts for
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From Fixed Grids to Moving Particles:A Transferable Latent Operator for Fluid Dynamics
Meng Li, Chuqi Chen, Zhengqing Gao +4
Lagrangian modeling is vital to fluid dynamics, as it characterizes particle transport and complements the Eulerian representation. However, Lagrangian trajectories are less common…
Learn Singularly Perturbed Solutions via Homotopy Dynamics
Chuqi Chen, Yahong Yang, Yang Xiang +1
Solving partial differential equations (PDEs) using neural networks has become a central focus in scientific machine learning. Training neural networks for singularly perturbed pro…
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations
Chuqi Chen, Yahong Yang, Yang Xiang +1
Neural network-based approaches have recently shown significant promise in solving partial differential equations (PDEs) in science and engineering, especially in scenarios featuri…
Stability Analysis Framework for Particle-based Distance GANs with Wasserstein Gradient Flow
Chuqi Chen, Yue Wu, Yang Xiang
In this paper, we investigate the training process of generative networks that use a type of probability density distance named particle-based distance as the objective function, e…
Elastic Interaction Energy-Based Generative Model: Approximation in Feature Space
Chuqi Chen, Yue Wu, Yang Xiang
In this paper, we propose a novel approach to generative modeling using a loss function based on elastic interaction energy (EIE), which is inspired by the elastic interaction betw…