Zobrazeno 1 - 10
of 67 019
pro vyhledávání: '"regularisation"'
We tackle the regularisation of a differential system related to generalised Krawtchouk polynomials. We show a straightforward connection between certain auxiliary quantities involving the recurrence coefficients of these polynomials and Painlev\'e V
Externí odkaz:
http://arxiv.org/abs/2411.18192
The mathematical consistency of the BMHV scheme of dimensional regularisation (DReg) comes at the cost of requiring symmetry-restoring counterterms to cancel the regularisation-induced breaking of gauge and BRST invariance. There is no unique way to
Externí odkaz:
http://arxiv.org/abs/2411.02543
In complex-valued coherent inverse problems such as synthetic aperture radar (SAR), one may often have prior information only on the magnitude image which shows the features of interest such as strength of reflectivity. In contrast, there may be no m
Externí odkaz:
http://arxiv.org/abs/2410.22161
The high-precision measurements of exoplanet transit light curves that are now available contain information about the planet properties, their orbital parameters, and stellar limb darkening (LD). Recent 3D magneto-hydrodynamical (MHD) simulations of
Externí odkaz:
http://arxiv.org/abs/2410.07636
Autor:
Miller, Thomas, Tam, Alexander K. Y., Marangell, Robert, Wechselberger, Martin, Bradshaw-Hajek, Bronwyn H.
We consider a general reaction--nonlinear-diffusion equation with a region of negative diffusivity, and show how a nonlinear regularisation selects a shock position. Negative diffusivity can model population aggregation, but leads to shock-fronted so
Externí odkaz:
http://arxiv.org/abs/2410.04106
Nonlinear constrained optimization has a wide range of practical applications. In this paper, we consider nonlinear optimization with inequality constraints. The interior point method is considered to be one of the most powerful algorithms for solvin
Externí odkaz:
http://arxiv.org/abs/2410.21070
Improving Automatic Speech Recognition with Decoder-Centric Regularisation in Encoder-Decoder Models
This paper proposes a simple yet effective way of regularising the encoder-decoder-based automatic speech recognition (ASR) models that enhance the robustness of the model and improve the generalisation to out-of-domain scenarios. The proposed approa
Externí odkaz:
http://arxiv.org/abs/2410.17437
Recent work developed convolutional deep kernel machines, achieving 92.7% test accuracy on CIFAR-10 using a ResNet-inspired architecture, which is SOTA for kernel methods. However, this still lags behind neural networks, which easily achieve over 94%
Externí odkaz:
http://arxiv.org/abs/2410.06171
Autor:
Vargas, Víctor Manuel, Gutiérrez, Pedro Antonio, Barbero-Gómez, Javier, Hervás-Martínez, César
An ordinal classification problem is one in which the target variable takes values on an ordinal scale. Nowadays, there are many of these problems associated with real-world tasks where it is crucial to accurately classify the extreme classes of the
Externí odkaz:
http://arxiv.org/abs/2407.12417
Autor:
Kluth, Yannick
We investigate $\beta$-functions of quantum gravity using dimensional regularisation. In contrast to minimal subtraction, a non-minimal renormalisation scheme is employed which is sensitive to power-law divergences from mass terms or dimensionful cou
Externí odkaz:
http://arxiv.org/abs/2409.09252