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A deformation-based framework for learning solution mappings of PDEs defined on varying domains
In this work, we establish a deformation-based framework for learning solution mappings of PDEs defined on varying domains. The union of functions def...
Dec 2, 2024
3 authors
279 views
A dual physics-informed neural network for topology optimization
We propose a novel dual physics-informed neural network for topology optimization (DPNN-TO), which merges physics-informed neural networks (PINNs) wit...
Oct 18, 2024
3 authors
105 views
Mitigating Stop-and-Go Traffic Congestion with Operator Learning
This paper presents a novel neural operator learning framework for designing boundary control to mitigate stop-and-go congestion on freeways. The free...
Nov 7, 2024
3 authors
213 views
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