Pages that link to "Item:Q2135816"

The following pages link to A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions (Q2135816):

Displaying 45 items.

• Data-driven discoveries of Bäcklund transformations and soliton evolution equations via deep neural network learning schemes (Q2081273) (← links)
• Data-driven solutions and parameter discovery of the Sasa-Satsuma equation via the physics-informed neural networks method (Q2083739) (← links)
• Prediction of the number of solitons for initial value of nonlinear Schrödinger equation based on the deep learning method (Q2107244) (← links)
• The nonlinear wave solutions and parameters discovery of the Lakshmanan-Porsezian-Daniel based on deep learning (Q2113140) (← links)
• \(N\)-double poles solutions for nonlocal Hirota equation with nonzero boundary conditions using Riemann-Hilbert method and PINN algorithm (Q2140112) (← links)
• Data-driven rogue waves and parameters discovery in nearly integrable \(\mathcal{PT}\)-symmetric Gross-Pitaevskii equations via PINNs deep learning (Q2167994) (← links)
• Conservative physics-informed neural networks on discrete domains for conservation laws: applications to forward and inverse problems (Q2184334) (← links)
• Mixed higher-order rogue waves and solitons for the coupled modified nonlinear Schrödinger equation (Q2677762) (← links)
• Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator (Q2679950) (← links)
• Physics-informed neural networks combined with polynomial interpolation to solve nonlinear partial differential equations (Q2682670) (← links)
• Physics-informed neural network methods based on Miura transformations and discovery of new localized wave solutions (Q2683577) (← links)
• Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures (Q2688074) (← links)
• Physics-informed neural networks based on adaptive weighted loss functions for Hamilton-Jacobi equations (Q2694112) (← links)
• A deep learning method for solving high-order nonlinear soliton equations (Q6039957) (← links)
• VC-PINN: variable coefficient physics-informed neural network for forward and inverse problems of PDEs with variable coefficient (Q6069931) (← links)
• A physics-constrained deep residual network for solving the sine-Gordon equation (Q6076683) (← links)
• Enforcing continuous symmetries in physics-informed neural network for solving forward and inverse problems of partial differential equations (Q6078492) (← links)
• Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs (Q6096531) (← links)
• Deep learning data-driven multi-soliton dynamics and parameters discovery for the fifth-order Kaup-Kuperschmidt equation (Q6096544) (← links)
• Number of solitons emerged in the initial profile of shallow water using convolutional neural networks (Q6130982) (← links)
• Pre-training physics-informed neural network with mixed sampling and its application in high-dimensional systems (Q6130985) (← links)
• Parallel physics-informed neural networks method with regularization strategies for the forward-inverse problems of the variable coefficient modified KdV equation (Q6130986) (← links)
• Physics-informed neural networks with two weighted loss function methods for interactions of two-dimensional oceanic internal solitary waves (Q6130987) (← links)
• Deep neural networks learning forward and inverse problems of two-dimensional nonlinear wave equations with rational solitons (Q6143642) (← links)
• Deep learning soliton dynamics and complex potentials recognition for 1D and 2D \(\mathcal{PT}\)-symmetric saturable nonlinear Schrödinger equations (Q6160033) (← links)
• Multi-output physics-informed neural network for one- and two-dimensional nonlinear time distributed-order models (Q6186170) (← links)
• Exploring two-dimensional internal waves: a new three-coupled Davey-Stewartson system and physics-informed neural networks with weight assignment methods (Q6191519) (← links)
• Gradient-enhanced physics-informed neural networks based on transfer learning for inverse problems of the variable coefficient differential equations (Q6191522) (← links)
• Is the neural tangent kernel of PINNs deep learning general partial differential equations always convergent? (Q6198233) (← links)
• Data-driven nonparametric identification of material behavior based on physics-informed neural network with full-field data (Q6201157) (← links)
• Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions (Q6202605) (← links)
• Two-stage initial-value iterative physics-informed neural networks for simulating solitary waves of nonlinear wave equations (Q6497269) (← links)
• Physical informed memory networks for solving PDEs: implementation and applications (Q6497869) (← links)
• \(PT\)-symmetric PINN for integrable nonlocal equations: forward and inverse problems (Q6554430) (← 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)
• Data-driven identification of the spectral operator in AKNS Lax pairs using conserved quantities (Q6573517) (← links)
• Deep learning-based method for solving seepage equation under unsteady boundary (Q6574145) (← links)
• Bright-dark rogue wave transition in coupled ab system via the physics-informed neural networks method (Q6574264) (← links)
• Darboux transformation-based LPNN generating novel localized wave solutions (Q6584190) (← links)
• A failure-informed multi-stage training algorithm for three-component nonlinear Schrödinger equation (Q6585366) (← links)
• E-PINN: extended physics informed neural network for the forward and inverse problems of high-order nonlinear integro-differential equations (Q6590587) (← links)
• Pseudo grid-based physics-informed convolutional-recurrent network solving the integrable nonlinear lattice equations (Q6599876) (← links)
• Novel localized wave of modified Kadomtsev-Petviashvili equation (Q6632888) (← links)
• Physics informed self-supervised segmentation of elastic composite materials (Q6641894) (← links)
• AsPINN: Adaptive symmetry-recomposition physics-informed neural networks (Q6643565) (← links)