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A Bayesian approach is developed to analyze change points in multivariate time series and space-time data. The methodology is used to assess the impact of extended inundation on the ecosystem of the Gulf Plains bioregion in northern…

Methodology · Statistics 2013-06-21 Chris Strickland , Robert Burdett , Robert Denham , Robert Kohn , Kerrie Mengersen

Recent studies have revealed synchronized multivalued behavior in thermodynamic, dynamical, and geometric quantities during the black hole first-order phase transition, which enables a diagnosis from different perspectives, yet its…

General Relativity and Quantum Cosmology · Physics 2026-03-16 Shi-Hao Zhang , Zi-Yuan Li , Jing-Fei Zhang , Xin Zhang

Clustering analysis identifies samples as groups based on either their mutual closeness or homogeneity. In order to detect clusters in arbitrary shapes, a novel and generic solution based on boundary erosion is proposed. The clusters are…

Computer Vision and Pattern Recognition · Computer Science 2018-04-16 Cheng-Hao Deng , Wan-Lei Zhao

Boundary detection is essential for a variety of computer vision tasks such as segmentation and recognition. In this paper we propose a unified formulation and a novel algorithm that are applicable to the detection of different types of…

Computer Vision and Pattern Recognition · Computer Science 2012-02-17 Marius Leordeanu , Rahul Sukthankar , Cristian Sminchisescu

Reconstructing the structural geology and mineral composition of the first few kilometers of the Earth's subsurface from sparse or indirect surface observations remains a long-standing challenge with critical applications in mineral…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Simon Ghyselincks , Valeriia Okhmak , Stefano Zampini , George Turkiyyah , David Keyes , Eldad Haber

We introduce a novel geometry-oriented methodology, based on the emerging tools of topological data analysis, into the change point detection framework. The key rationale is that change points are likely to be associated with changes in…

Machine Learning · Statistics 2019-10-30 Umar Islambekov , Monisha Yuvaraj , Yulia R. Gel

The study of phase transitions using data-driven approaches is challenging, especially when little prior knowledge of the system is available. Topological data analysis is an emerging framework for characterizing the shape of data and has…

Statistical Mechanics · Physics 2021-05-26 Quoc Hoan Tran , Mark Chen , Yoshihiko Hasegawa

Dynamical phase transitions are defined as non-analytic points of the large deviation function of current fluctuations. We show that for boundary driven systems, many dynamical phase transitions can be identified using the geometrical…

Statistical Mechanics · Physics 2017-12-13 Ohad Shpielberg

Understanding the principles of geophysical phenomena is an essential and challenging task. "Model-driven" approaches have supported the development of geophysics for a long time; however, such methods suffer from the curse of…

Geophysics · Physics 2020-09-30 Siwei Yu , Jianwei Ma

3D point clouds of natural environments relevant to problems in geomorphology often require classification of the data into elementary relevant classes. A typical example is the separation of riparian vegetation from ground in fluvial…

Computer Vision and Pattern Recognition · Computer Science 2012-01-25 Nicolas Brodu , Dimitri Lague

Rockfall detection is a crucial procedure in the field of geology, which helps to reduce the associated risks. Currently, geologists identify rockfall events almost manually utilizing point cloud and imagery data obtained from different…

Machine Learning · Computer Science 2022-09-29 Thanasis Zoumpekas , Anna Puig , Maria Salamó , David García-Sellés , Laura Blanco Nuñez , Marta Guinau

Mineral exploration in biogeochemistry is related to the detection of anomalies in soil, which is driven by many factors and thus a complex problem. Mik\v{s}ov\'a, Rieser, and Filzmoser (2019) have introduced a method for the identification…

Airborne magnetic data are commonly used to produce preliminary geological maps. Machine learning has the potential to partly fulfill this task rapidly and objectively, as geological mapping is comparable to a semantic segmentation problem.…

Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an…

Computational Physics · Physics 2022-08-10 Hao Wu , Sarah Greer , Daniel O'Malley

We identify a new "order parameter" for the disorder driven many-body localization (MBL) transition by leveraging artificial intelligence. This allows us to pin down the transition, as the point at which the physics changes qualitatively,…

Quantum Physics · Physics 2019-11-19 Patrick Huembeli , Alexandre Dauphin , Peter Wittek , Christian Gogolin

Topology identification and inference of processes evolving over graphs arise in timely applications involving brain, transportation, financial, power, as well as social and information networks. This chapter provides an overview of graph…

Signal Processing · Electrical Eng. & Systems 2025-12-12 Gonzalo Mateos , Yanning Shen , Georgios B. Giannakis , Ananthram Swami

Landscape paradigm is ubiquitous in physics and other natural sciences, but it has to be supplemented with both quantitative and qualitatively meaningful tools for analyzing the topography of a given landscape. We here consider dynamic…

Statistical Mechanics · Physics 2009-11-10 Jean-Pierre Aubin , Annick Lesne

We present a novel method for predicting binary phase diagrams through the automatic construction of a minimal basis set of representative templates. The core assumption is that any materials space can be divided into a small number of…

Materials Science · Physics 2024-10-03 Caja Annweiler , Simone Di Cataldo , Maurits W. Haverkort , Lilia Boeri

One of the first steps during the investigation of geological objects is the interwell correlation. It provides information on the structure of the objects under study, as it comprises the framework for constructing geological models and…

We propose lacunarity as a novel recurrence quantification measure and illustrate its efficacy to detect dynamical regime transitions which are exhibited by many complex real-world systems. We carry out a recurrence plot based analysis for…

Data Analysis, Statistics and Probability · Physics 2021-01-26 Tobias Braun , Vishnu R. Unni , R. I. Sujith , Juergen Kurths , Norbert Marwan