Zobrazeno 1 - 10
of 345
pro vyhledávání: '"Cheng, Kevin P."'
Quantum signal processing (QSP) is a methodology for constructing polynomial transformations of a linear operator encoded in a unitary. Applied to an encoding of a state $\rho$, QSP enables the evaluation of nonlinear functions of the form $\text{tr}
Externí odkaz:
http://arxiv.org/abs/2409.19043
Autor:
Buckleton, John, Susik, Mateusz, Curran, James M., Cheng, Kevin, Taylor, Duncan, Bright, Jo-Anne, Kelly, Hannah, Wivell, Richard
There is interest in comparing the output, principally the likelihood ratio, from the two probabilistic genotyping software EuroForMix (EFM) and STRmix. Many of these comparison studies are descriptive and make little or no effort to diagnose the cau
Externí odkaz:
http://arxiv.org/abs/2307.00015
Contactless 3D finger knuckle patterns have emerged as an effective biometric identifier due to its discriminativeness, visibility from a distance, and convenience. Recent research has developed a deep feature collaboration network which simultaneous
Externí odkaz:
http://arxiv.org/abs/2301.02934
Publikováno v:
IEEE Transactions on Signal Processing (2023), volume 71, pages 3164 - 3178
We consider probabilistic models for sequential observations which exhibit gradual transitions among a finite number of states. We are particularly motivated by applications such as human activity analysis where observed accelerometer time series con
Externí odkaz:
http://arxiv.org/abs/2210.01918
We discuss a range of miscodes found in probabilistic genotyping (PG) software and from other industries that have been reported in the literature and have been used to inform PG admissibility hearings. Every instance of the discovery of a miscode in
Externí odkaz:
http://arxiv.org/abs/2205.09788
Deep neural networks (DNNs) have been successfully applied to many real-world problems, but a complete understanding of their dynamical and computational principles is still lacking. Conventional theoretical frameworks for analysing DNNs often assume
Externí odkaz:
http://arxiv.org/abs/2203.12967
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks. Benefitted from the maturing camera sensors, single-modal (RGB) and multi-modal (e.g., RGB+Depth) FAS has been applied in various scenarios wi
Externí odkaz:
http://arxiv.org/abs/2202.08192
Many time series can be modeled as a sequence of segments representing high-level discrete states, such as running and walking in a human activity application. Flexible models should describe the system state and observations in stationary "pure-stat
Externí odkaz:
http://arxiv.org/abs/2110.06741
Learning in deep neural networks (DNNs) is implemented through minimizing a highly non-convex loss function, typically by a stochastic gradient descent (SGD) method. This learning process can effectively find good wide minima without being trapped in
Externí odkaz:
http://arxiv.org/abs/2009.10588
Non-parametric and distribution-free two-sample tests have been the foundation of many change point detection algorithms. However, randomness in the test statistic as a function of time makes them susceptible to false positives and localization ambig
Externí odkaz:
http://arxiv.org/abs/2006.05539