Allen--Cahn
PulseAugur coverage of Allen--Cahn — every cluster mentioning Allen--Cahn across labs, papers, and developer communities, ranked by signal.
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Fourier spectral differentiation offers significant speedup for physics-informed neural networks
A new research paper compares two methods for calculating spatial derivatives in physics-informed neural networks (PINNs): automatic differentiation (AD) and Fourier spectral differentiation. The study found that Fourie…
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Deflation-PINNs framework identifies multiple PDE solutions using neural networks
Researchers have developed Deflation-PINNs, a novel framework that integrates physics-informed neural networks (PINNs) with Deep Operator Networks (DeepONets) to address the challenge of identifying multiple solutions f…
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New TGSR-PINN method enhances physics-informed neural network transfer learning
Researchers have developed a new method called Target-Guided Selective Reweighting PINN (TGSR-PINN) to improve the transfer learning capabilities of physics-informed neural networks (PINNs) for inverse problems. This ap…
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Fourier Neural Operators Achieve Learning Guarantees for Dissipative Equations
Researchers have established approximation and learning guarantees for Fourier Neural Operators (FNOs) when applied to time-T solution operators of dissipative evolution equations. The analysis demonstrates that FNOs ca…