Pages that link to "Item:Q1710361"
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The following pages link to Machine learning for graph-based representations of three-dimensional discrete fracture networks (Q1710361):
Displaying 12 items.
- Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics (Q1629734) (← links)
- Random neighborhood graphs as models of fracture networks on rocks: structural and dynamical analysis (Q1740109) (← links)
- Parametric generation of conditional geological realizations using generative neural networks (Q2009823) (← links)
- Machine learning for flux regression in discrete fracture networks (Q2059207) (← links)
- Multilevel graph partitioning for three-dimensional discrete fracture network flow simulations (Q2066832) (← links)
- Physics-informed machine learning for backbone identification in discrete fracture networks (Q2192818) (← links)
- Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways (Q2321886) (← links)
- A Probabilistic Clustering Approach for Identifying Primary Subnetworks of Discrete Fracture Networks with Quantified Uncertainty (Q3296919) (← links)
- Identifying Backbones in Three-Dimensional Discrete Fracture Networks: A Bipartite Graph-Based Approach (Q4627440) (← links)
- Parallel Meshing, Discretization, and Computation of Flow in Massive Discrete Fracture Networks (Q5230630) (← links)
- Fracture network flow prediction with uncertainty using physics-informed graph features (Q6181714) (← links)
- A multi-aggregator graph neural network for backbone exaction of fracture networks (Q6578301) (← links)
