Pages that link to "Item:Q2095535"
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The following pages link to Adaptive machine learning-based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery (Q2095535):
Displaying 8 items.
- Adaptive ensemble-based optimisation for petrophysical inversion (Q2040683) (← links)
- An intelligent multi-fidelity surrogate-assisted multi-objective reservoir production optimization method based on transfer stacking (Q2085102) (← links)
- Adjoint-based surrogate optimization of oil reservoir water flooding (Q2357904) (← links)
- A machine-learning-accelerated distributed LBFGS method for field development optimization: algorithm, validation, and applications (Q6074257) (← links)
- Optimization problems for PDEs in weak space-time form. Abstracts from the workshop held March 5--10, 2023 (Q6076083) (← links)
- A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs (Q6097873) (← links)
- Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery (Q6392682) (← links)
- Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems (Q6667327) (← links)
