Deep reinforcement learning for adaptive mesh refinement
Finite element discretizations of problems in computational physics often rely on adaptive mesh refinement (AMR) to preferentially resolve regions containing important features during simulation. However, these spatial refinement strategies are often heuristic and rely on domain-specific knowledge o...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/1721.1/153763 |