Pages that link to "Item:Q2684140"
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The following pages link to Data-driven forward-inverse problems for Yajima-Oikawa system using deep learning with parameter regularization (Q2684140):
Displaying 8 items.
- Data-driven rogue waves and parameters discovery in nearly integrable \(\mathcal{PT}\)-symmetric Gross-Pitaevskii equations via PINNs deep learning (Q2167994) (← links)
- Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures (Q2688074) (← links)
- Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs (Q6096531) (← links)
- Physics-informed ConvNet: learning physical field from a shallow neural network (Q6199712) (← links)
- Lump wave solutions, lump-stripe soliton inelastic collision phenomena and rogue-type wave solutions for a generalized breaking soliton system in \((3+1)\)-dimensions (Q6203142) (← links)
- Data-driven forward-inverse problems for Yajima-Oikawa system using deep learning with parameter regularization (Q6385076) (← links)
- Breather wave solutions on the Weierstrass elliptic periodic background for the \((2 + 1)\)-dimensional generalized variable-coefficient KdV equation (Q6545646) (← links)
- Darboux transformation-based LPNN generating novel localized wave solutions (Q6584190) (← links)
