Pages that link to "Item:Q2175100"
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The following pages link to Propagation of uncertainty in the mechanical and biological response of growing tissues using multi-fidelity Gaussian process regression (Q2175100):
Displaying 10 items.
- Statistical test for anomalous diffusion based on empirical anomaly measure for Gaussian processes (Q2076159) (← links)
- Monte Carlo fPINNs: deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations (Q2083146) (← links)
- Model-data-driven constitutive responses: application to a multiscale computational framework (Q2234818) (← links)
- Predicting the mechanical properties of biopolymer gels using neural networks trained on discrete fiber network data (Q2246386) (← links)
- Editorial: Special issue on uncertainty quantification, machine learning, and data-driven modeling of biological systems (Q2310243) (← links)
- Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: application to planar soft tissues (Q2678528) (← links)
- Discriminating Gaussian processes via quadratic form statistics (Q5000843) (← links)
- Data-driven computational method for growth-induced deformation problems of soft materials (Q6181794) (← links)
- Testing of two-dimensional Gaussian processes by sample cross-covariance function (Q6550005) (← links)
- Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of a time fractional equation (Q6630929) (← links)
