Hybrid quantum-classical model with quantum feature encoding and clustering outperforms classical neural networks for LPBF melt pool prediction.
Variational Quantum Algorithms for Computational Fluid Dynamics
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
quant-ph 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
A survey of variational quantum algorithms, quantum neural networks, and tensor networks for addressing scalability challenges in computational fluid dynamics.
citing papers explorer
-
A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion
Hybrid quantum-classical model with quantum feature encoding and clustering outperforms classical neural networks for LPBF melt pool prediction.
-
A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics
A survey of variational quantum algorithms, quantum neural networks, and tensor networks for addressing scalability challenges in computational fluid dynamics.