Pages that link to "Item:Q6096443"
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The following pages link to Probabilistic neural data fusion for learning from an arbitrary number of multi-fidelity data sets (Q6096443):
Displaying 4 items.
- Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression (Q5162361) (← links)
- A framework for strategic discovery of credible neural network surrogate models under uncertainty (Q6557831) (← links)
- Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity (Q6584871) (← links)
- Bayesian neural networks for predicting uncertainty in full-field material response (Q6663292) (← links)
