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We present a method to compute the stochastic reachability safety probabilities for high-dimensional stochastic dynamical systems. Our approach takes advantage of a nonparametric learning technique known as conditional distribution…

Systems and Control · Electrical Eng. & Systems 2020-10-19 Adam J. Thorpe , Vignesh Sivaramakrishnan , Meeko M. K. Oishi

Co-designing a robot's morphology and control can ensure synergistic interactions between them, prevalent in biological organisms. However, co-design is a high-dimensional search problem. To make this search tractable, we need a systematic…

Robotics · Computer Science 2026-04-14 Apoorv Vaish , Oliver Brock

Completely randomized experiment is the gold standard for causal inference. When the covariate information for each experimental candidate is available, one typical way is to include them in covariate adjustments for more accurate treatment…

Methodology · Statistics 2025-06-10 Xin Lu , Fan Yang , Yuhao Wang

The paper analyzes the rotation averaging problem as a minimization problem for a potential function of the corresponding gradient system. This dynamical system is one generalization of the famous Kuramoto model on special orthogonal group…

Computer Vision and Pattern Recognition · Computer Science 2021-11-25 Zinaid Kapić , Aladin Crnkić , Vladimir Jaćimović , Nevena Mijajlović

In many important statistical analyses, the number of covariates $p$ often exceeds the data size $n$, a regime commonly referred to as high-dimensional. While considerable progress has been made in high-dimensional regression under the…

Methodology · Statistics 2026-05-29 Herman Tesso , Georges Nguefack-Tsague

In this paper we propose a class of weighted rank correlation coefficients extending the Spearman's rho. The proposed class constructed by giving suitable weights to the distance between two sets of ranks to place more emphasis on items…

Statistics Theory · Mathematics 2020-01-22 M. Sanatgar , A. Dolati , M. Amini

This study proposes a new constraint handling technique for assisting metaheuristic optimization algorithms to solve constrained optimization problems more effectively and efficiently. Given any two solutions of any constrained optimization…

Optimization and Control · Mathematics 2023-10-23 Ting Huang , Qiang Zhang , Witold Pedrycz , Shanlin Yang

One of the simplest mathematical models in the study of nonlinear systems is the Kuramoto model, which describes synchronization in systems from swarms of insects to superconductors. We have recently found a connection between the original,…

This paper presents a significant advancement in the estimation of the Composite Link Model within a penalized likelihood framework, specifically designed to address indirect observations of grouped count data. While the model is effective…

Methodology · Statistics 2025-12-16 Carlo G. Camarda , María Durbán

Pseudospectral analysis is fundamental for quantifying the sensitivity and transient behavior of nonnormal matrices, yet its computational cost scales cubically with dimension, rendering it prohibitive for large-scale systems. While…

Numerical Analysis · Mathematics 2026-02-03 Vladimir R. Kostic , Dragana Lj. Cvetkovic , Ljiljana Cvetkovic

In this paper, we study the complete synchronization of the Kuramoto model with general network containing a spanning tree, when the initial phases are distributed in an open half circle. As lack of uniform coercivity in general digraph, in…

Dynamical Systems · Mathematics 2021-07-15 Xiongtao Zhang , Tingting Zhu

In this paper we develop non-asymptotic Gaussian approximation results for the sampling distribution of suprema of empirical processes when the indexing function class $\mathcal{F}_n$ varies with the sample size $n$ and may not be Donsker.…

Statistics Theory · Mathematics 2023-09-06 Alexander Giessing

Synchronization and desynchronization are the two ends on the spectrum of emergent phenomena that somehow often coexist in biological, neuronal, and physical networks. However, previous studies essentially regard their coexistence as a…

Adaptation and Self-Organizing Systems · Physics 2023-05-18 Chongzhi Wang , Haibin Shao , Dewei Li

Multivariate generalized Gamma convolutions are distributions defined by a convolutional semi-parametric structure. Their flexible dependence structures, the marginal possibilities and their useful convolutional expression make them…

Statistics Theory · Mathematics 2022-03-28 Oskar Laverny

We propose a pseudo-structural framework for analyzing contemporaneous co-movements in reduced-rank matrix autoregressive (RRMAR) models. Unlike conventional vector-autoregressive (VAR) models that would discard the matrix structure, our…

Econometrics · Economics 2025-09-25 Alain Hecq , Ivan Ricardo , Ines Wilms

Networks with different levels of interactions, including multilayer and multiplex networks, can display a rich diversity of dynamical behaviors and can be used to model and study a wide range of systems. Despite numerous efforts to…

Dynamical Systems · Mathematics 2023-10-09 Priya B. Jain , Tung T. Nguyen , Ján Mináč , Lyle E. Muller , Roberto C. Budzinski

Higher order interactions can lead to new equilibrium states and bifurcations in systems of coupled oscillators described by the Kuramoto model. However, even in the simplest case of 3-body interactions there are more than one possible…

Physics and Society · Physics 2025-05-21 Guilherme S. Costa , Marcel Novaes , Marcus A. M. de Aguiar

We study synchronization in a Kuramoto model of globally coupled phase oscillators with a bi-harmonic coupling function, in the thermodynamic limit of large populations. We develop a method for an analytic solution of self-consistent…

Chaotic Dynamics · Physics 2015-06-19 M. Komarov , A. Pikovsky

We investigate in detail the topological gauged Wess-Zumino-Witten models describing topological Kazama-Suzuki models based on complex Grassmannians. We show that there is a topological sector in which the ring of observables (constructed…

High Energy Physics - Theory · Physics 2009-10-28 Matthias Blau , Faheem Hussain , George Thompson

We propose methodology for statistical inference for low-dimensional parameters of sparse precision matrices in a high-dimensional setting. Our method leads to a non-sparse estimator of the precision matrix whose entries have a Gaussian…

Statistics Theory · Mathematics 2015-08-13 Jana Jankova , Sara van de Geer