NeTMY neural fields with annealed encoding, multiscale optimization, and spectrum-fidelity losses achieve superior localization and distributional accuracy in NV-center inverse sensing by using a tensor power-summed dipolar operator that exposes and mitigates center-collapse failures.
Ridge regression: Biased estimation for nonorthogonal problems
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Extreme Quantum Cognition Machines combine quantum reservoir-style evolution with a dynamical attention mechanism in the Hamiltonian to produce robust nonlinear embeddings for decision making from noisy training data.
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Neural Fields for NV-Center Inverse Sensing
NeTMY neural fields with annealed encoding, multiscale optimization, and spectrum-fidelity losses achieve superior localization and distributional accuracy in NV-center inverse sensing by using a tensor power-summed dipolar operator that exposes and mitigates center-collapse failures.
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Extreme Quantum Cognition Machines for Deliberative Decision Making
Extreme Quantum Cognition Machines combine quantum reservoir-style evolution with a dynamical attention mechanism in the Hamiltonian to produce robust nonlinear embeddings for decision making from noisy training data.