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The microscopic framework of time-dependent covariant density functional theory is applied to study multinucleon transfer reactions, with transfer probabilities calculated using the particle number projection method. It is found that…

Nuclear Theory · Physics 2024-02-23 D. D. Zhang , D. Vretenar , T. NikšIć , P. W. Zhao , J. Meng

The spectrum of mutations in a collection of cancer genomes can be described by a mixture of a few mutational signatures. The mutational signatures can be found using non-negative matrix factorization (NMF). To extract the mutational…

Methodology · Statistics 2022-11-02 Marta Pelizzola , Ragnhild Laursen , Asger Hobolth

In this article, we derive statistical tools to analyze and distinguish the patterns of genetic variability produced by classical and recent population genetic models related to seed banks. In particular, we are concerned with models…

Populations and Evolution · Quantitative Biology 2020-01-10 Jochen Blath , Eugenio Buzzoni , Jere Koskela , Maite Wilke Berenguer

Statistical dependence between hypotheses poses a significant challenge to the stability of large scale multiple hypotheses testing. Ignoring it often results in an unacceptably large spread in the false positive proportion even though the…

Methodology · Statistics 2018-10-15 Sairam Rayaprolu , Zhiyi Chi

Dependency functions of dependent variables are relevant for i) performing uncertainty quantification and sensitivity analysis in presence of dependent variables and/or correlated variables, and ii) simulating random dependent variables. In…

Methodology · Statistics 2022-03-22 Matieyendou Lamboni

We consider the error distribution in functional linear models with scalar response and functional covariate. Different asymptotic expansions of the empirical distribution function and the empirical characteristic function based on…

Methodology · Statistics 2025-12-01 Natalie Neumeyer , Leonie Selk

We develop a theory for waveform-diverse moving-target synthetic-aperture radar, in the case in which a single moving antenna is used for both transmitting and receiving. We assume that the targets (scattering objects) are moving linearly,…

Classical Physics · Physics 2011-05-17 Margaret Cheney , Brett Borden

Non-stationary source separation is a well-established branch of blind source separation with many different methods. However, for none of these methods large-sample results are available. To bridge this gap, we develop large-sample theory…

Statistics Theory · Mathematics 2024-09-10 François Bachoc , Christoph Muehlmann , Klaus Nordhausen , Joni Virta

The distribution of genetic polymorphisms in a population contains information about the mutation rate and the strength of natural selection at a locus. Here, we show that the Poisson Random Field (PRF) method of population-genetic…

Populations and Evolution · Quantitative Biology 2007-07-18 Michael M Desai , Joshua B. Plotkin

In this paper we provide new methodology for inference of the geometric features of a multivariate density in deconvolution. Our approach is based on multiscale tests to detect significant directional derivatives of the unknown density at…

Methodology · Statistics 2016-11-21 Konstantin Eckle , Nicolai Bissantz , Holger Dette

The stochastic density functional theory (sDFT) has exhibited advantages over the standard Kohn-Sham DFT method and has become an attractive approach for large-scale electronic structure calculations. The sDFT method avoids the expensive…

Computational Physics · Physics 2025-12-08 Xue Quan , Huajie Chen

Extracting genetic information from a full range of sequencing data is important for understanding diseases. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type. We…

Genomics · Quantitative Biology 2018-10-10 Zexian Zeng , Andy Vo , Chengsheng Mao , Susan E Clare , Seema A Khan , Yuan Luo

Diffusion models (DMs) represent state-of-the-art generative models for continuous inputs. DMs work by constructing a Stochastic Differential Equation (SDE) in the input space (ie, position space), and using a neural network to reverse it.…

Machine Learning · Computer Science 2024-05-14 Tianrong Chen , Jiatao Gu , Laurent Dinh , Evangelos A. Theodorou , Joshua Susskind , Shuangfei Zhai

This paper presents a study of power series distributions (PSD) with prescribed covariance characteristics. Such distributions constitute a fundamental class in probability theory and mathematical statistics, as they generalize a wide range…

Statistics Theory · Mathematics 2025-12-23 Oleksandr Volkov , Yurii Volkov , Nataliia Voinalovych

The paper investigates the rich class of Generalized Tempered Stable distribution, an alternative to Normal distribution and the $\alpha$-Stable distribution for modelling asset return and many physical and economic systems. Firstly, we…

Statistical Finance · Quantitative Finance 2022-06-07 A. H. Nzokem , V. T. Montshiwa

Frequency synthesis (FS) is a technique vital for all kinds of radio frequency (RF) communications, such as: mobile phones, Bluetooth, Wi-Fi, radio, TV and satellite, and in other equipment requiring periodic signals of stable and…

Signal Processing · Electrical Eng. & Systems 2019-02-27 Mario Stipčević

While covariance matrices have been widely studied in many scientific fields, relatively limited progress has been made on estimating conditional covariances that permits a large covariance matrix to vary with high-dimensional subject-level…

Methodology · Statistics 2025-05-28 Rakheon Kim , Jingfei Zhang

Most theoretical tools available for the analysis of spreading processes over networks assume exponentially distributed transmission and recovery times. In practice, the empirical distribution of transmission times for many real spreading…

Social and Information Networks · Computer Science 2016-11-04 Masaki Ogura , Victor M. Preciado

In this paper, we investigate the latent geometry of generative diffusion models under the manifold hypothesis. For this purpose, we analyze the spectrum of eigenvalues (and singular values) of the Jacobian of the score function, whose…

Machine Learning · Statistics 2025-04-14 Enrico Ventura , Beatrice Achilli , Gianluigi Silvestri , Carlo Lucibello , Luca Ambrogioni

Large-scale density functional theory (DFT) calculations provide a powerful tool to investigate the atomic and electronic structure of materials with complex structures. This article reviews a large-scale DFT calculation method, the…

Materials Science · Physics 2022-08-31 Ayako Nakata , David R. Bowler , Tsuyoshi Miyazaki