17 citations · 50 across the 9 of their papers we have counts for
5 papers · 1 filter
Factorized Neural Implicit DMD for Parametric Dynamics
Siyuan Chen, Zhecheng Wang, Yixin Chen +4
A data-driven, model-free approach to modeling the temporal evolution of physical systems mitigates the need for explicit knowledge of the governing equations. Even when physical p…
Learning Neural Constitutive Laws From Motion Observations for Generalizable PDE Dynamics
Pingchuan Ma, Peter Yichen Chen, Bolei Deng +4
We propose a hybrid neural network (NN) and PDE approach for learning generalizable PDE dynamics from motion observations. Many NN approaches learn an end-to-end model that implici…
Implicit Neural Spatial Representations for Time-dependent PDEs
Honglin Chen, Rundi Wu, Eitan Grinspun +2
Implicit Neural Spatial Representation (INSR) has emerged as an effective representation of spatially-dependent vector fields. This work explores solving time-dependent PDEs with I…
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho +6
The long runtime of high-fidelity partial differential equation (PDE) solvers makes them unsuitable for time-critical applications. We propose to accelerate PDE solvers using reduc…
Model reduction for the material point method via an implicit neural representation of the deformation map
Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun +1
This work proposes a model-reduction approach for the material point method on nonlinear manifolds. Our technique approximates the by approximating the deform…