Pages that link to "Item:Q6175124"
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The following pages link to Failure-Informed Adaptive Sampling for PINNs (Q6175124):
Displaying 23 items.
- HRW: Hybrid Residual and Weak Form Loss for Solving Elliptic Interface Problems with Neural Network (Q6151336) (← links)
- PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations (Q6151340) (← links)
- Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions (Q6171154) (← links)
- Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations (Q6187659) (← links)
- Less Emphasis on Hard Regions: Curriculum Learning of PINNs for Singularly Perturbed Convection-Diffusion-Reaction Problems (Q6192635) (← links)
- Correcting model misspecification in physics-informed neural networks (PINNs) (Q6497270) (← links)
- Render unto numerics: orthogonal polynomial neural operator for PDEs with nonperiodic boundary conditions (Q6575342) (← links)
- Solving Poisson problems in polygonal domains with singularity enriched physics informed neural networks (Q6585303) (← links)
- Domain decomposition learning methods for solving elliptic problems (Q6585310) (← links)
- Plasma-simulation physics informed neural networks (PS-PINNs) for global discharge models (Q6586304) (← links)
- Failure-informed adaptive sampling for PINNs. II: Combining with re-sampling and subset simulation (Q6593776) (← links)
- Deep finite volume method for partial differential equations (Q6615033) (← links)
- An accurate and efficient continuity-preserved method based on randomized neural networks for elliptic interface problems (Q6623701) (← links)
- A new method to compute the blood flow equations using the physics-informed neural operator (Q6639295) (← links)
- Deep adaptive sampling for surrogate modeling without labeled data (Q6639518) (← links)
- MHDnet: physics-preserving learning for solving magnetohydrodynamics problems (Q6646462) (← links)
- A neural particle method with interface tracking and adaptive particle refinement for free surface flows (Q6646467) (← links)
- Loss jump during loss switch in solving PDEs with neural networks (Q6646469) (← links)
- Efficiently training physics-informed neural networks via anomaly-aware optimization (Q6662394) (← links)
- Deep mixed residual method for solving PDE-constrained optimization problems (Q6663447) (← links)
- Adaptive operator learning for infinite-dimensional Bayesian inverse problems (Q6669407) (← links)
- Time integration schemes based on neural networks for solving partial differential equations on coarse grids (Q6670111) (← links)
- Annealed adaptive importance sampling method in PINNs for solving high dimensional partial differential equations (Q6670734) (← links)
