Pages that link to "Item:Q2206129"
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The following pages link to Learning physics by data for the motion of a sphere falling in a non-Newtonian fluid (Q2206129):
Displaying 10 items.
- Data-driven modeling for the motion of a sphere falling through a non-Newtonian fluid (Q1749579) (← links)
- An iterated quasi-interpolation approach for derivative approximation (Q2192583) (← links)
- PDE-Net 2.0: learning PDEs from data with a numeric-symbolic hybrid deep network (Q2222627) (← links)
- High-order numerical solution of time-dependent differential equations with quasi-interpolation (Q2273081) (← links)
- Probabilistic solutions to DAEs learning from physical data (Q5016828) (← links)
- High order multiquadric trigonometric quasi-interpolation method for solving time-dependent partial differential equations (Q6109897) (← links)
- A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid (Q6121825) (← links)
- Learning the nonlinear flux function of a hidden scalar conservation law from data (Q6145277) (← links)
- On mathematical modeling in image reconstruction and beyond (Q6200218) (← links)
- Gabor-filtered Fourier neural operator for solving partial differential equations (Q6566939) (← links)
