A 1-D CNN with novel multi-stage spectral attention mechanisms and adjustable class-balanced focal loss improves recognition accuracy on real ship-radiated noise datasets.
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Entanglement structure provides a natural distributed representation for quantum wavefunctions that reduces Hamiltonian applications to local contractions and enables near-linear scaling in simulations.
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Modulation Feature Enhancement with a Multi-Stage Attention Network for Underwater Acoustic Target Recognition
A 1-D CNN with novel multi-stage spectral attention mechanisms and adjustable class-balanced focal loss improves recognition accuracy on real ship-radiated noise datasets.
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Entanglement-informed distributed wavefunction approach to scalable quantum many-body systems
Entanglement structure provides a natural distributed representation for quantum wavefunctions that reduces Hamiltonian applications to local contractions and enables near-linear scaling in simulations.