Pages that link to "Item:Q2184334"

The following pages link to Conservative physics-informed neural networks on discrete domains for conservation laws: applications to forward and inverse problems (Q2184334):

Displaying 50 items.

• SeismicNET: physics-informed neural networks for seismic wave modeling in semi-infinite domain (Q6137634) (← links)
• A Rate of Convergence of Weak Adversarial Neural Networks for the Second Order Parabolic PDEs (Q6143000) (← links)
• Learning Specialized Activation Functions for Physics-Informed Neural Networks (Q6143615) (← links)
• Label-free learning of elliptic partial differential equation solvers with generalizability across boundary value problems (Q6146999) (← links)
• Identification of the flux function of nonlinear conservation laws with variable parameters (Q6156252) (← links)
• Numerical computation of partial differential equations by hidden-layer concatenated extreme learning machine (Q6159015) (← links)
• Discovery of PDEs driven by data with sharp gradient or discontinuity (Q6161547) (← links)
• Posteriori error neural network: a recovery type posteriori error estimator based on neural network for diffusion problems (Q6162471) (← links)
• PINN-FORM: a new physics-informed neural network for reliability analysis with partial differential equation (Q6171227) (← links)
• Distributed PINN for Linear Elasticity — A Unified Approach for Smooth, Singular, Compressible and Incompressible Media (Q6172992) (← links)
• Adaptive Learning Rate Residual Network Based on Physics-Informed for Solving Partial Differential Equations (Q6173072) (← links)
• Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks (Q6173359) (← links)
• A learned conservative semi-Lagrangian finite volume scheme for transport simulations (Q6173366) (← links)
• Discontinuity computing using physics-informed neural networks (Q6184289) (← links)
• Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression (Q6185193) (← links)
• High Order Deep Domain Decomposition Method for Solving High Frequency Interface Problems (Q6188658) (← links)
• An Adaptive Physics-Informed Neural Network with Two-Stage Learning Strategy to Solve Partial Differential Equations (Q6191768) (← links)
• Spectral operator learning for parametric PDEs without data reliance (Q6194143) (← links)
• Learning the Dynamics for Unknown Hyperbolic Conservation Laws Using Deep Neural Networks (Q6195013) (← links)
• wPINNs: Weak Physics Informed Neural Networks for Approximating Entropy Solutions of Hyperbolic Conservation Laws (Q6197777) (← links)
• Learning physical models that can respect conservation laws (Q6198203) (← links)
• Data-driven Whitney forms for structure-preserving control volume analysis (Q6202128) (← links)
• CNN-DP: composite neural network with differential propagation for impulsive nonlinear dynamics (Q6202143) (← links)
• Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions (Q6202605) (← links)
• Adaptive loss weighting auxiliary output fPINNs for solving fractional partial integro-differential equations (Q6496475) (← links)
• Correcting model misspecification in physics-informed neural networks (PINNs) (Q6497270) (← links)
• Splitting physics-informed neural networks for inferring the dynamics of integer- and fractional-order neuron models (Q6537067) (← links)
• A deep learning method for computing mean exit time excited by weak Gaussian noise (Q6539426) (← links)
• Gradient auxiliary physics-informed neural network for nonlinear biharmonic equation (Q6540123) (← links)
• RiemannONets: interpretable neural operators for Riemann problems (Q6550161) (← links)
• Anti-derivatives approximator for enhancing physics-informed neural networks (Q6550163) (← links)
• Solving the non-local Fokker-Planck equations by deep learning (Q6551384) (← links)
• Adaptive deep Fourier residual method via overlapping domain decomposition (Q6557761) (← links)
• On the locality of local neural operator in learning fluid dynamics (Q6557796) (← links)
• CEENs: causality-enforced evolutional networks for solving time-dependent partial differential equations (Q6557798) (← links)
• Physics-informed parallel neural networks with self-adaptive loss weighting for the identification of continuous structural systems (Q6557810) (← links)
• The data-driven rogue waves of the Hirota equation by using mix-training PINNs approach (Q6558868) (← links)
• Physics-informed neural networks and functional interpolation for stiff chemical kinetics (Q6565148) (← links)
• Data-driven physics-informed neural networks: a digital twin perspective (Q6566046) (← links)
• Learning scattering waves via coupling physics-informed neural networks and their convergence analysis (Q6567300) (← links)
• TDOR-MPINNs: multi-output physics-informed neural networks based on time differential order reduction for solving coupled Klein-Gordon-Zakharov systems (Q6568897) (← links)
• Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains (Q6569914) (← links)
• Neuro-PINN: a hybrid framework for efficient nonlinear projection equation solutions (Q6569923) (← links)
• The line rogue wave solutions of the nonlocal Davey-Stewartson I equation with \textit{PT} symmetry based on the improved physics-informed neural network (Q6571797) (← links)
• Non-diffusive neural network method for hyperbolic conservation laws (Q6572177) (← links)
• Bright-dark rogue wave transition in coupled ab system via the physics-informed neural networks method (Q6574264) (← links)
• PINN enhanced extended multiscale finite element method for fast mechanical analysis of heterogeneous materials (Q6576389) (← links)
• Domain decomposition learning methods for solving elliptic problems (Q6585310) (← links)
• Adaptive sampling points based multi-scale residual network for solving partial differential equations (Q6585372) (← links)
• Phase-field modeling of fracture with physics-informed deep learning (Q6588261) (← links)