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We introduce a new computational framework for estimating parameters in generalized generalized linear models (GGLM), a class of models that extends the popular generalized linear models (GLM) to account for dependencies among observations…

Methodology · Statistics 2023-04-28 Anatoli Juditsky , Arkadi Nemirovski , Yao Xie , Chen Xu

Stochastic Gradient Langevin Dynamics (SGLD) is a popular variant of Stochastic Gradient Descent, where properly scaled isotropic Gaussian noise is added to an unbiased estimate of the gradient at each iteration. This modest change allows…

Machine Learning · Computer Science 2017-06-06 Maxim Raginsky , Alexander Rakhlin , Matus Telgarsky

We show that Mellin moments of generalized parton distributions, given as even polynomials in the skewness parameter, are obtained from the Taylor expansion of light front wave functions. Furthermore, we derive non-standard versions of the…

High Energy Physics - Phenomenology · Physics 2017-11-29 Dieter Müller

Following Boukai (2021) we present the Generalized Gamma (GG) distribution as a possible RND for modeling European options prices under Heston's (1993) stochastic volatility (SV) model. This distribution is seen as especially useful in…

Computational Finance · Quantitative Finance 2021-08-24 Ben Boukai

The generalized Pareto distribution (GPD) is a fundamental model for analyzing the tail behavior of a distribution. In particular, the shape parameter of the GPD characterizes the extremal properties of the distribution. As described in…

Methodology · Statistics 2026-02-18 Takuma Yoshida , Koki Momoki , Shuichi Kawano

We present a calculation of the twist-3 generalized parton distributions (GPDs) for gluons in the proton. Our analysis is performed within a light-front constituent model where the proton is treated as a two-body state of a spin-1 gluon and…

High Energy Physics - Phenomenology · Physics 2025-10-07 Parashmani Thakuria , Madhurjya Lalung , Jayanta Kumar Sarma

We present a parametrization of the chiral even generalized parton distributions, $H$, $E$, $\widetilde{H}$, $\widetilde{E}$, for the quark, antiquark and gluon, in the perturbative QCD-parton framework. Parametric analytic forms are given…

High Energy Physics - Phenomenology · Physics 2022-04-13 Brandon Kriesten , Philip Velie , Emma Yeats , Fernanda Yepez Lopez , Simonetta Liuti

A long and slender finger can serve as a simple ``test bed'' for different phase ordering models. In this work, the globally-conserved, interface-controlled dynamics of a long finger is investigated, analytically and numerically, in two…

Disordered Systems and Neural Networks · Physics 2009-11-07 Avner Peleg , Baruch Meerson , Arkady Vilenkin , Massimo Conti

We study systems with a crossover parameter lambda, such as the temperature T, which has a threshold value lambda* across which the correlation function changes from exhibiting fixed wavelength (or time period) modulations to continuously…

Statistical Mechanics · Physics 2015-02-25 Saurish Chakrabarty , Vladimir Dobrosavljevic , Alexander Seidel , Zohar Nussinov

Generalised parton distributions (GPDs) and transverse momentum dependent parton distributions (TMDs) describe complementary aspects of the three-dimensional structure of hadrons. We discuss their relation to each other and recall important…

High Energy Physics - Phenomenology · Physics 2016-06-22 Markus Diehl

In this paper, we introduce a new extension of the generalized linear failure rate distributions. It includes some well-known lifetime distributions such as extension of generalized exponential and generalized linear failure rate…

Statistics Theory · Mathematics 2016-03-10 Mohammad Reza Kazemi , Ali Akbar Jafari , Saeid Tahmasebi

Generalised Parton Distributions (GPDs) provide multidimensional insight into hadron structure and are particularly relevant for the pion, whose dynamics are intimately linked to chiral symmetry breaking. We introduce a novel modelling…

High Energy Physics - Phenomenology · Physics 2026-03-19 J. M. Morgado-Chávez , J. Segovia , F. de Soto , J. Rodríguez-Quintero , V. Bertone , M. Defurne , C. Mezrag , H. Moutarde

We investigate the helicity dependent generalized parton distributions (GPDs) in momentum as well as transverse position (impact) spaces for up and down quarks in a proton when the momentum transfer in both the transverse and longitudinal…

High Energy Physics - Phenomenology · Physics 2017-09-28 Chandan Mondal

This paper studies the application of the generalized method of moments (GMM) to multi-reference alignment (MRA): the problem of estimating a signal from its circularly-translated and noisy copies. We begin by proving that the GMM estimator…

Signal Processing · Electrical Eng. & Systems 2022-04-06 Asaf Abas , Tamir Bendory , Nir Sharon

We phenomenologically constrain the small-$x$ and small-$\xi$ gluon generalized parton distributions (GPDs) with the deeply virtual $J/\psi$ production (DV$J/\psi$P) in the framework of GPDs through universal moment parameterization (GUMP).…

High Energy Physics - Phenomenology · Physics 2024-12-03 Yuxun Guo , Xiangdong Ji , M. Gabriel Santiago , Jinghong Yang , Hao-Cheng Zhang

We investigate the generalized parton distributions (GPDs) with non-zero $\xi$ and $\Delta^\perp$ for a relativistic spin-1/2 composite system, namely for an electron dressed with a photon, in light-front framework by expressing them in…

High Energy Physics - Phenomenology · Physics 2009-11-11 D. Chakrabarti , A. Mukherjee

Several generalizations of the logistic distribution, and certain related models, are proposed by many authors for modeling various random phenomena such as those encountered in data engineering, pattern recognition, and reliability…

Statistics Theory · Mathematics 2019-03-19 Seema S Nair , Nicy Sebastian

We report on the use of Feynman-Hellmann techniques to calculate the off-forward Compton amplitude (OFCA) in lattice QCD. At leading-twist, the Euclidean OFCA is parameterised by the Mellin moments of generalised parton distributions…

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this…

Machine Learning · Statistics 2017-02-28 Olivier Bachem , Mario Lucic , S. Hamed Hassani , Andreas Krause

Generalized parton distributions (GPDs) offer a comprehensive picture of the nucleon structure and dynamics and provide a link between microscopic and macroscopic properties of the nucleon. These quantities, which can be interpreted as the…

Nuclear Experiment · Physics 2014-11-20 E. Voutier
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