A least squares finite element method to multi-species modeling of negative DC corona discharges in point-to-plane configurations. [PDF]
Majazi S +3 more
europepmc +1 more source
Partial Differential Equations in Action: From Modelling to Theory
semanticscholar +1 more source
Robust Inverse Material Design With Physical Guarantees Using the Voigt‐Reuss Net
ABSTRACT We apply the Voigt‐Reuss net, a spectrally normalized neural surrogate introduced in [38], for forward and inverse mechanical homogenization with a key guarantee that all predicted effective stiffness tensors satisfy Voigt‐Reuss bounds in the Löwner sense during training, inference, and gradient‐driven optimization.
Sanath Keshav, Felix Fritzen
wiley +1 more source
Hybrid expansion methods for fractional non-linear mathematical systems with Erdelyi-Kober derivative operators in theory of tsunami wave modeling. [PDF]
Damag FH +5 more
europepmc +1 more source
Optimal error estimates of the diffuse domain method for second order parabolic equations. [PDF]
Hao W, Ju L, Xu Y.
europepmc +1 more source
Introduction: Big data and partial differential equations†
Yves van Gennip, C. Schönlieb
semanticscholar +1 more source
A locally adaptive regularization of a hybrid variational model for color image diffusion via integration of diffusion with normalized data. [PDF]
Arain MB +6 more
europepmc +1 more source
MHA-PINN: A Novel Physics-Informed Neural Network for Predicting Fiber Dyeability. [PDF]
Zhou F +5 more
europepmc +1 more source
Physics-Informed Neural Networks with Unknown Partial Differential Equations: An Application in Multivariate Time Series. [PDF]
Mortezanejad SAF +2 more
europepmc +1 more source
Quantum-informed machine learning for predicting spatiotemporal chaos with practical quantum advantage. [PDF]
Wang M, Xue X, Gao M, Coveney PV.
europepmc +1 more source

