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Graphs are a powerful representation tool in machine learning applications, with link prediction being a key task in graph learning. Temporal link prediction in dynamic networks is of particular interest due to its potential for solving…

Machine Learning · Computer Science 2024-01-17 Sanaz Hasanzadeh Fard , Mohammad Ghassemi

We analyze the rate of convergence of the local statistics of Dyson Brownian motion to the GOE/GUE for short times $t=o(1)$ with deterministic initial data V . Our main result states that if the density of states of $V$ is bounded both…

Probability · Mathematics 2016-02-05 Benjamin Landon , Horng-Tzer Yau

Although many studies collect biomedical time series signals from multiple subjects, there is a dearth of models and methods for assessing the association between frequency domain properties of time series and other study outcomes. This…

Applications · Statistics 2015-03-13 Robert T. Krafty , Martica Hall

Due to their conjugate posteriors, Gaussian process priors are attractive for estimating the drift of stochastic differential equations with continuous time observations. However, their performance strongly depends on the choice of the…

Statistics Theory · Mathematics 2020-02-04 Jan van Waaij

In this work, we propose an efficient two-stage algorithm solving a joint problem of correlation detection and partial alignment recovery between two Gaussian databases. Correlation detection is a hypothesis testing problem; under the null…

Information Theory · Computer Science 2023-05-26 Ran Tamir

For discrete panel data, the dynamic relationship between successive observations is often of interest. We consider a dynamic probit model for short panel data. A problem with estimating the dynamic parameter of interest is that the model…

Methodology · Statistics 2014-09-30 Wei Gao , Wicher Bergsma , Qiwei Yao

Brownian particles in random potentials show an extended regime of subdiffusive dynamics at intermediate times. The asymptotic diffusive behavior is often established at very long times and thus cannot be accessed in experiments or…

Soft Condensed Matter · Physics 2014-05-22 Richard D. L. Hanes , Michael Schmiedeberg , Stefan U. Egelhaaf

Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest. While existing correlation measures are suitable for discovering average correlation, they fail to discover hidden or…

Machine Learning · Statistics 2017-11-22 Hyeji Kim , Weihao Gao , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

We study interacting systems of linear Brownian motions whose drift vector at every time point is determined by the relative ranks of the coordinate processes at that time. Our main objective has been to study the long range behavior of the…

Probability · Mathematics 2008-01-22 Soumik Pal , Jim Pitman

We study the numerical evaluation of several functions appearing in the small time expansion of the distribution of the time-integral of the geometric Brownian motion as well as its joint distribution with the terminal value of the…

Probability · Mathematics 2024-05-21 Peter Nandori , Dan Pirjol

This study introduces a new metric called ''DynamicScore'' to evaluate the dynamics of graphs. It can be applied to both vertices and edges. Unlike traditional metrics, DynamicScore not only measures changes in the number of vertices or…

Discrete Mathematics · Computer Science 2023-09-12 Vincent Bridonneau , Frédéric Guinand , Yoann Pigné

Detecting changes in high-dimensional vectors presents significant challenges, especially when the post-change distribution is unknown and time-varying. This paper introduces a novel robust algorithm for correlation change detection in…

Methodology · Statistics 2024-10-07 Assma Alghamdi , Taposh Banerjee , Jayant Rajgopal

The paper focuses on the Vasicek model driven by a tempered fractional Brownian motion. We derive the asymptotic distributions of the least-squares estimators (based on continuous-time observations) for the unknown drift parameters. This…

Statistics Theory · Mathematics 2024-06-06 Yuliya Mishura , Kostiantyn Ralchenko , Olena Dehtiar

A comparative study of different block matching alternatives for motion estimation is presented. The study is focused on computational burden and objective measures on the accuracy of prediction. Together with existing algorithms several…

Computer Vision and Pattern Recognition · Computer Science 2022-02-25 Marcos Faundez-Zanuy , Francesc Tarres-Ruiz

A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips, and enables the evolution of…

Data Analysis, Statistics and Probability · Physics 2012-08-09 Tomislav Stankovski , Andrea Duggento , Peter V. E. McClintock , Aneta Stefanovska

We study the 2D motion of colloidal dimers by single-particle tracking and compare the experimental observations obtained by bright-field microscopy to theoretical predictions for anisotropic diffusion. The comparison is based on the…

In this work, building up on [1] we present momentum space Ward identities related to broken higher spin symmetry as an alternate approach to computing correlators of spinning operators in interacting theories such as the quasi-fermionic…

High Energy Physics - Theory · Physics 2021-07-28 Sachin Jain , Renjan Rajan John , Vinay Malvimat

We generalize the methods used in the theory of correlation dynamics and establish a set of equations of motion for many-body correlation green's functions in the non-relativistic case. These non-linear and coupled equations of motion…

Nuclear Theory · Physics 2015-06-26 Shun-Jin Wang , Wei Zuo , Wolfgang Cassing

Cyber-physical systems often consist of entities that interact with each other over time. Meanwhile, as part of the continued digitization of industrial processes, various sensor technologies are deployed that enable us to record…

Machine Learning · Computer Science 2018-09-03 Razvan-Gabriel Cirstea , Darius-Valer Micu , Gabriel-Marcel Muresan , Chenjuan Guo , Bin Yang

I present a new improved estimator for the correlation function of 2D nonlinear sigma models. Numerical tests for the 2D XY model and the 2D O(3)-invariant vector model were performed. For small physical volume, i.e. a lattice size small…

High Energy Physics - Lattice · Physics 2010-12-01 Martin Hasenbusch
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