Pages that link to "Item:Q2096255"

The following pages link to Efficient coupled deep neural networks for the time-dependent coupled Stokes-Darcy problems (Q2096255):

Displaying 10 items.

• CPINNs: a coupled physics-informed neural networks for the closed-loop geothermal system (Q2682678) (← links)
• AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems (Q5099843) (← links)
• Multi-Scale Deep Neural Network (MscaleDNN) Methods for Oscillatory Stokes Flows in Complex Domains (Q5162374) (← links)
• The robust physics-informed neural networks for a typical fourth-order phase field model (Q6103706) (← links)
• A second-order time parallel decoupled algorithm for the Stokes/Darcy model (Q6494186) (← links)
• PDNNs: the parallel deep neural networks for the Navier-Stokes equations coupled with heat equation (Q6537439) (← links)
• Optimal long time error estimates of a second-order decoupled finite element method for the Stokes-Darcy problem (Q6543597) (← links)
• Exponential synchronisation for delayed Clifford-valued coupled switched neural networks via static event-triggering rule (Q6544828) (← links)
• The coupled physical-informed neural networks for the two phase magnetohydrodynamic flows (Q6549888) (← links)
• A deep learning method for incompressible fluid equations and the coupling problems (Q6665361) (← links)