Pages that link to "Item:Q6076683"
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The following pages link to A physics-constrained deep residual network for solving the sine-Gordon equation (Q6076683):
Displaying 10 items.
- PINN deep learning method for the Chen-Lee-Liu equation: rogue wave on the periodic background (Q2060632) (← links)
- Data-driven rogue waves and parameters discovery in nearly integrable \(\mathcal{PT}\)-symmetric Gross-Pitaevskii equations via PINNs deep learning (Q2167994) (← links)
- Physics informed by deep learning: numerical solutions of modified Korteweg-de Vries equation (Q2244291) (← links)
- A deep learning method for solving high-order nonlinear soliton equations (Q6039957) (← links)
- Higher-order smooth positons and breather positons of Sine-Gordon equation (Q6039972) (← links)
- The D’Alembert type waves and the soliton molecules in a (2+1)-dimensional Kadomtsev-Petviashvili with its hierarchy equation* (Q6046357) (← links)
- Deep learning soliton dynamics and complex potentials recognition for 1D and 2D \(\mathcal{PT}\)-symmetric saturable nonlinear Schrödinger equations (Q6160033) (← links)
- Data-driven fusion and fission solutions in the Hirota-Satsuma-Ito equation via the physics-informed neural networks method (Q6497884) (← links)
- The traveling wave solutions of the perturbed double Sine-Gordon equation (Q6584773) (← links)
- Pseudo grid-based physics-informed convolutional-recurrent network solving the integrable nonlinear lattice equations (Q6599876) (← links)
