English
Related papers

Related papers: Parity-expanded variational analysis for non-zero …

200 papers

Parity-violating quasielastic electron scattering is studied within the context of the relativistic Fermi gas and its extensions to include the effects of pionic correlations and meson-exchange currents. The work builds on previous studies…

Nuclear Theory · Physics 2009-10-22 M. B. Barbaro , A. De Pace , T. W. Donnelly , A. Molinari

Electrical discharge machining (EDM) is a crucial process in precision manufacturing, leveraging electro-thermal energy to remove material without electrode contact. In this study, we delve into the realm of Machine Learning (ML) to enhance…

Mesoscale and Nanoscale Physics · Physics 2026-05-15 Mohsen Asghari Ilani , Yaser Mike Banad

We propose a black-box variational inference method to approximate intractable distributions with an increasingly rich approximating class. Our method, termed variational boosting, iteratively refines an existing variational approximation…

Machine Learning · Statistics 2017-02-21 Andrew C. Miller , Nicholas Foti , Ryan P. Adams

Principal component analysis (PCA) frequently suffers from the disturbance of outliers and thus a spectrum of robust extensions and variations of PCA have been developed. However, existing extensions of PCA treat all samples equally even…

Machine Learning · Computer Science 2021-03-23 Rui Zhang , Hongyuan Zhang , Xuelong Li

Measurements of parity-violating longitudinal analyzing powers (normalized asymmetries) in polarized proton-proton scattering provide a unique window on the interplay between the weak and strong interactions between and within hadrons.…

Nuclear Experiment · Physics 2015-06-26 W. T. H. van Oers , for E497 collaboration

A statistical approach based on the interval analysis (IA) is proposed for the analysis of the effects, on the radiation patterns radiated by phased arrays, of random errors and tolerances in the amplitudes and phases of the array-elements…

Signal Processing · Electrical Eng. & Systems 2021-02-10 P. Rocca , N. Anselmi , A. Benoni , A. Massa

Signal recovery from unitarily invariant measurements is investigated in this paper. A message-passing algorithm is formulated on the basis of expectation propagation (EP). A rigorous analysis is presented for the dynamics of the algorithm…

Information Theory · Computer Science 2019-05-22 Keigo Takeuchi

By looking at the parity-nonconserving (PNC) asymmetries at different energies in $\vec{p} p$ scattering, it is in principle possible to determine the PNC $\rho NN$ and $\omega NN$ couplings of a single-meson-exchange model of the PNC $NN$…

Nuclear Theory · Physics 2009-11-11 C. -P. Liu , C. H. Hyun , B. Desplanques

Non-negative tensor factorization models enable predictive analysis on count data. Among them, Bayesian Poisson-Gamma models can derive full posterior distributions of latent factors and are less sensitive to sparse count data. However,…

Machine Learning · Computer Science 2020-12-15 Yuan Jin , Ming Liu , Yunfeng Li , Ruohua Xu , Lan Du , Longxiang Gao , Yong Xiang

This paper describes a method to do ab initio molecular dynamics in electronically excited systems within the random phase approximation (RPA). Using a dynamical variational treatment of the RPA frequency, which corresponds to the…

Condensed Matter · Physics 2009-10-31 Eric R. Bittner , D. S. Kosov

A clear need for automatic anomaly detection applied to automotive testing has emerged as more and more attention is paid to the data recorded and manual evaluation by humans reaches its capacity. Such real-world data is massive, diverse,…

Machine Learning · Computer Science 2024-11-22 Lucas Correia , Jan-Christoph Goos , Philipp Klein , Thomas Bäck , Anna V. Kononova

The operator product expansion (OPE), truncated in dimension, is employed in many contexts. An example is the extraction of the strong coupling, $\alpha_s$, from hadronic $\tau$-decay data, using a variety of analysis methods based on…

High Energy Physics - Phenomenology · Physics 2019-10-16 Diogo Boito , Maarten Golterman , Kim Maltman , Santiago Peris

We use Bayes' probability theorem to analyze many-pole fits of hadron propagators. An alternative method of estimating values and uncertainties of the fit parameters is offered, which has certain advantages over the conventional methods.…

High Energy Physics - Lattice · Physics 2009-10-28 David Makovoz

We present several different types of multivariate statistical techniques used in the measurement of the inclusive top pair production cross section in $p \bar{p}$-collisions at $\sqrt{s} = 1.96 \text{TeV}$ employing the full RunII data…

High Energy Physics - Experiment · Physics 2014-12-15 Jiří Franc , Petr Bouř , Michal Štěpánek , Václav Kůs

A general framework for principal component analysis (PCA) in the presence of heteroskedastic noise is introduced. We propose an algorithm called HeteroPCA, which involves iteratively imputing the diagonal entries of the sample covariance…

Statistics Theory · Mathematics 2021-04-02 Anru R. Zhang , T. Tony Cai , Yihong Wu

This paper investigates the resource allocation design for a pinching antenna (PA)-assisted multiuser multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system featuring multiple dielectric waveguides. To enhance…

Signal Processing · Electrical Eng. & Systems 2025-10-31 Shaokang Hu , Ruotong Zhao , Yihuan Liao , Derrick Wing Kwan Ng , Jinhong Yuan

Recently, the binary expansion testing framework was introduced to test the independence of two continuous random variables by utilizing symmetry statistics that are complete sufficient statistics for dependence. We develop a new test based…

Statistics Theory · Mathematics 2021-01-11 Duyeol Lee , Kai Zhang , Michael R. Kosorok

Lattice results, kinematical constraints and QCD dispersion relations are combined for the first time to derive model-independent bounds for QCD form factors and corresponding rates. To take into account the error bars on the lattice…

High Energy Physics - Phenomenology · Physics 2011-05-05 Laurent Lellouch

Current variational inference methods for hierarchical Bayesian nonparametric models can neither characterize the correlation structure among latent variables due to the mean-field setting, nor infer the true posterior dimension because of…

Machine Learning · Statistics 2022-04-07 Yirui Liu , Xinghao Qiao , Jessica Lam

We develop a coherent framework for integrative simultaneous analysis of the exploration-exploitation and model order selection trade-offs. We improve over our preceding results on the same subject (Seldin et al., 2011) by combining…

Machine Learning · Computer Science 2015-03-19 Yevgeny Seldin , Nicolò Cesa-Bianchi , François Laviolette , Peter Auer , John Shawe-Taylor , Jan Peters
‹ Prev 1 8 9 10 Next ›