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Related papers: Path Coupling and Aggregate Path Coupling

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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

The key in agglomerative clustering is to define the affinity measure between two sets. A novel agglomerative clustering method is proposed by utilizing the path integral to define the affinity measure. Firstly, the path integral descriptor…

Computer Vision and Pattern Recognition · Computer Science 2015-08-10 Wei-Ya Ren , Shuo-Hao Li , Qiang Guo , Guo-Hui Li , Jun Zhang

Simulating transition dynamics between metastable states is a fundamental challenge in dynamical systems and stochastic processes with wide real-world applications in understanding protein folding, chemical reactions and neural activities.…

Machine Learning · Computer Science 2024-10-22 Haibo Wang , Yuxuan Qiu , Yanze Wang , Rob Brekelmans , Yuanqi Du

Clustering mixed data presents numerous challenges inherent to the very heterogeneous nature of the variables. A clustering algorithm should be able, despite of this heterogeneity, to extract discriminant pieces of information from the…

Machine Learning · Computer Science 2022-05-10 Robin Fuchs , Denys Pommeret , Cinzia Viroli

Since many physical laws -- from classical mechanics to electromagnetism -- are formulated as two-body interactions, the same perspective naturally extends to biological and social dynamics. Here we focus on rhythmic phenomena, where phase…

Adaptation and Self-Organizing Systems · Physics 2025-08-26 Ryosuke Yoneda , Haruma Furukawa , Daigo Fujiwara , Toshio Aoyagi

Glauber dynamics is a powerful tool to generate randomized, approximate solutions to combinatorially difficult problems. Applications include Markov Chain Monte Carlo (MCMC) simulation and distributed scheduling for wireless networks. In…

Probability · Mathematics 2010-04-06 Mathieu Leconte , Jian Ni , R. Srikant

Gaussian process (GP) models provide a powerful tool for prediction but are computationally prohibitive using large data sets. In such scenarios, one has to resort to approximate methods. We derive an approximation based on a composite…

Machine Learning · Statistics 2018-02-02 Xiuming Liu , Dave Zachariah , Edith C. H. Ngai

The study of the rare transitions that take place between long lived metastable states is a major challenge in molecular dynamics simulations. Many of the methods suggested to address this problem rely on the identification of the slow…

Chemical Physics · Physics 2023-06-07 Dhiman Ray , Enrico Trizio , Michele Parrinello

Practical Bayesian learning often requires (1) online inference, (2) dynamic models, and (3) ensembling over multiple different models. Recent advances have shown how to use random feature approximations to achieve scalable, online…

Machine Learning · Computer Science 2024-05-03 Daniel Waxman , Petar M. Djurić

We give a systematic development of the application of matrix norms to rapid mixing in spin systems. We show that rapid mixing of both random update Glauber dynamics and systematic scan Glauber dynamics occurs if any matrix norm of the…

Probability · Mathematics 2009-03-06 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

The dynamics of coupled intermittent maps is used to model the correlated structure of genomic sequences. The use of intermittent maps, as opposed to other simple chaotic maps, is particularly suited for the production of long range…

Statistical Mechanics · Physics 2015-06-05 Astero Provata , Christian Beck

In an effort to effectively model observed patterns in the spatial configuration of individuals of multiple species in nature, we introduce the saturated pairwise interaction Gibbs point process. Its main strength lies in its ability to…

Methodology · Statistics 2023-02-27 Ian Flint , Nick Golding , Peter Vesk , Yan Wang , Aihua Xia

Networks of coupled phase oscillators are one of the most studied dynamical systems with numerous applications in physics, chemistry, biology, and engineering. Their behaviour is often characterized by the emergence of various partially…

Pattern Formation and Solitons · Physics 2026-02-27 Oleh E. Omel'chenko

The reaction-coordinate mapping is a useful technique to study complex quantum dissipative dynamics into structured environments. In essence, it aims to mimic the original problem by means of an 'augmented system', which includes a suitably…

Quantum Physics · Physics 2019-09-11 Luis A. Correa , Buqing Xu , Benjamin Morris , Gerardo Adesso

A foremost challenge in modern network science is the inverse problem of reconstruction (inference) of coupling equations and network topology from the measurements of the network dynamics. Of particular interest are the methods that can…

Chaotic Dynamics · Physics 2019-10-31 Isao T. Tokuda , Zoran Levnajic , Kazuyoshi Ishimura

The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to…

Robotics · Computer Science 2022-03-21 Hyung-Jin Yoon , Chuyuan Tao , Hunmin Kim , Naira Hovakimyan , Petros Voulgaris

Optimizing paths on networks is crucial for many applications, from subway traffic to Internet communication. As global path optimization that takes account of all path-choices simultaneously is computationally hard, most existing routing…

Physics and Society · Physics 2013-09-05 Chi Ho Yeung , David Saad , K. Y. Michael Wong

Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing…

Quantitative Methods · Quantitative Biology 2016-04-29 Jonathan U. Harrison , Christian A. Yates

Solute trapping is an important phenomenon in rapid solidification of alloys, for which the continuous growth model (CGM) is a popular sharp interface theory. Using matched asymptotic analysis, we show how to quantitatively map the sharp…

Materials Science · Physics 2018-09-17 Tatu Pinomaa , Nikolas Provatas

The maximum independent set (MIS) problem is a well-studied combinatorial optimization problem that naturally arises in many applications, such as wireless communication, information theory and statistical mechanics. MIS problem is NP-hard,…

Discrete Mathematics · Computer Science 2015-04-20 Rémi Varloot , Ana Bušić , Anne Bouillard