Results 271 to 280 of about 275,582 (319)
Unbiased calculation, evaluation, and calibration of ensemble forecast anomalies
Standard methods for calculating ensemble forecast anomalies result in statistical inconsistencies between forecast and verification anomalies, even if the underlying forecasts are perfectly reliable. An unbiased evaluation of anomaly‐based ensemble forecasts must account for differences in climatological sampling uncertainty between forecasts and ...
Christopher D. Roberts+1 more
wiley +1 more source
Tunable optical nonreciprocity in double-cavity optomechanical system with nonreciprocal coupling. [PDF]
Mao M, Jiang H, Kong C, Liu J.
europepmc +1 more source
Adaptive weighted progressive iterative approximation based on coordinate decomposition. [PDF]
Liu Y, Wang Y, Liu C.
europepmc +1 more source
The hybrid approach to Quantum Supervised Machine Learning is compatible with Noisy Intermediate Scale Quantum (NISQ) devices but hardly useful. Pure quantum kernels requiring fault‐tolerant quantum computers are more promising. Examples are kernels computed by means of the Quantum Fourier Transform (QFT) and kernels defined via the calculation of ...
Massimiliano Incudini+2 more
wiley +1 more source
Knot data analysis using multiscale Gauss link integral. [PDF]
Shen L+5 more
europepmc +1 more source
Advantage of Non‐Gaussian Operations in Phase Estimation via Mach–Zehnder Interferometer
This research delves into the advantages rendered by probabilistic non‐Gaussian operations in phase estimation, using Mach–Zehnder interferometers with difference‐intensity and parity detection measurement schemes. An experimentally viable scheme is considered to implement three distinct non‐Gaussian operations, namely, photon subtraction, photon ...
Manali Verma+3 more
wiley +1 more source
An analytic proof of the stable reduction theorem. [PDF]
Song J, Sturm J, Wang X.
europepmc +1 more source
What can we Learn from Quantum Convolutional Neural Networks?
Quantum Convolutional Neural Networks have been long touted as one of the premium architectures for quantum machine learning (QML). But what exactly makes them so successful for tasks involving quantum data? This study unlocks some of these mysteries; particularly highlighting how quantum data embedding provides a basis for superior performance in ...
Chukwudubem Umeano+3 more
wiley +1 more source
Operator means, barycenters, and fixed point equations. [PDF]
Virosztek D.
europepmc +1 more source