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Expectation-Maximization (EM) algorithm is a widely used iterative algorithm for computing (local) maximum likelihood estimate (MLE). It can be used in an extensive range of problems, including the clustering of data based on the Gaussian…

Machine Learning · Statistics 2023-03-28 Pierre Houdouin , Esa Ollila , Frederic Pascal

The stochastic motions of a diffusing particle contain information concerning the particle's interactions with binding partners and with its local environment. However, accurate determination of the underlying diffusive properties, beyond…

Biological Physics · Physics 2016-12-21 Peter K. Koo , Simon G. J. Mochrie

Using two different approaches, we perform updated and detailed calculations of the complete one-loop (Next-to-Leading Order (NLO)) set of electroweak radiative corrections to the parity violating e- e- -> e- e- (gamma) scattering…

High Energy Physics - Phenomenology · Physics 2011-08-18 A. Aleksejevs , S. Barkanova , A. Ilyichev , Y. Kolomensky , V. Zykunov

This paper derives the nonparametric maximum likelihood estimator (NPMLE) of a distribution function from observations which are subject to both bias and censoring. The NPMLE is obtained by a simple EM algorithm which is an extension of the…

Statistics Theory · Mathematics 2007-08-22 Micha Mandel

We set up Restricted Boltzmann Machines (RBM) to reproduce the Long Range Ising (LRI) models of the Ohmic type in one dimension. The RBM parameters are tuned by using the standard machine learning procedure with an additional method of…

Statistical Mechanics · Physics 2017-01-03 Ken-Ichi Aoki , Tamao Kobayashi

Numerical mode matching (NMM) methods are widely used for analyzing wave propagation and scattering in structures that are piece-wise uniform along one spatial direction. For open structures that are unbounded in transverse directions…

Numerical Analysis · Mathematics 2018-04-24 Wangtao Lu , Ya Yan Lu , Dawei Song

We propose a multilevel Markov chain Monte Carlo (MCMC) method for the Bayesian inference of random field parameters in PDEs using high-resolution data. Compared to existing multilevel MCMC methods, we additionally consider level-dependent…

Numerical Analysis · Mathematics 2025-08-19 Pieter Vanmechelen , Geert Lombaert , Giovanni Samaey

Efficient sampling from the Boltzmann distribution given its energy function is a key challenge for modeling complex physical systems such as molecules. Boltzmann Generators address this problem by leveraging continuous normalizing flows to…

Machine Learning · Computer Science 2025-10-17 Rishal Aggarwal , Jacky Chen , Nicholas M. Boffi , David Ryan Koes

This short communication uses a simple experiment to show that fitting to a power law distribution by using graphical methods based on linear fit on the log-log scale is biased and inaccurate. It shows that using maximum likelihood…

Statistical Mechanics · Physics 2009-11-10 Michel L. Goldstein , Steven A. Morris , Gary G. Yen

We propose an adaptive estimator for the stationary distribution of a bifurcating Markov Chain on $\mathbb R^d$. Bifurcating Markov chains (BMC for short) are a class of stochastic processes indexed by regular binary trees. A kernel…

Statistics Theory · Mathematics 2017-06-22 S Valere Bitseki Penda , Angelina Roche

We propose a novel numerical approach for nonlocal diffusion equations [8] with integrable kernels, based on the relationship between the backward Kolmogorov equation and backward stochastic differential equations (BSDEs) driven by L\`{e}vy…

Numerical Analysis · Mathematics 2015-07-28 Guannan Zhang , Weidong Zhao , Clayton Webster , Max Gunzburger

At low reduced electric fields the electron energy distribution function in heavy noble gases can take two distinct shapes. This "bistability effect" - in which electron-electron (Coulomb) collisions play an essential role - is analyzed…

Plasma Physics · Physics 2015-06-16 Nikolay Dyatko , Zoltan Donko

A numerical realization of an elastic beam lattice is used to obtain scaling exponents relevant to the extent of damage within the controlled, catastrophic and total regimes of mode-I brittle fracture. The relative fraction of damage at the…

Soft Condensed Matter · Physics 2007-09-12 Bjorn Skjetne , Torbjorn Helle , Alex Hansen

The spin-boson model has nontrivial quantum phase transitions in the sub-Ohmic regime. For the bath spectra exponent $0 \leqslant s<1/2$, the bosonic numerical renormalization group (BNRG) study of the exponents $\beta$ and $\delta$ are…

Strongly Correlated Electrons · Physics 2012-04-27 Ning-Hua Tong , Yan-Hua Hou

We investigate the stability under variation of the renormalization, factorization and energy scales entering the calculation of the cross section, at next-to-leading order in the BFKL formalism, for the production of Mueller-Navelet jets…

High Energy Physics - Phenomenology · Physics 2015-06-16 F. Caporale , B. Murdaca , A. Sabio Vera , C. Salas

Machine learning interatomic potentials (MLIPs) are routinely used to model diverse atomistic phenomena, yet parameterizing them to accurately capture solid-state phase transformations remains difficult. We present error metrics and…

Materials Science · Physics 2026-01-21 Lorenzo Piersante , Anirudh Raju Natarajan

We study the problem of distributed adaptive estimation over networks where nodes cooperate to estimate physical parameters that can vary over both space and time domains. We use a set of basis functions to characterize the space-varying…

Systems and Control · Computer Science 2015-07-22 Reza Abdolee , Benoit Champagne , Ali H. Sayed

Recent developments in matrix-product-state (MPS) investigations of many-body localization (MBL) are reviewed, with a discussion of benefits and limitations of the method. This approach allows one to explore the physics around the MBL…

Disordered Systems and Neural Networks · Physics 2022-04-29 Elmer V. H. Doggen , Igor V. Gornyi , Alexander D. Mirlin , Dmitry G. Polyakov

Mixed-effects models are widely used to model data with hierarchical grouping structures and high-cardinality categorical predictor variables. However, for high-dimensional crossed random effects, current standard computations relying on…

Methodology · Statistics 2026-05-15 Pascal Kündig , Fabio Sigrist

The $B$-meson light-cone distribution amplitude is an important non-perturbative quantity arising in the factorization of the amplitudes for many exclusive decays of $B$ mesons, such as $B^-\to\gamma\,\ell^-\bar\nu$. We reconsider the…

High Energy Physics - Phenomenology · Physics 2022-03-17 Anne Mareike Galda , Matthias Neubert , Xing Wang