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Comparing weighted networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted…

Applications · Statistics 2014-03-28 Cedric E. Ginestet , Arnaud P. Fournel , Andrew Simmons

Non-Gaussianities of dynamical origin are disentangled from primordial ones using the formalism of large deviation statistics with spherical collapse dynamics. This is achieved by relying on accurate analytical predictions for the one-point…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-27 Cora Uhlemann , Enrico Pajer , Christophe Pichon , Takahiro Nishimichi , Sandrine Codis , Francis Bernardeau

We report the first ensemble results from the FUSE survey of molecular hydrogen in lines of sight with A_V $\gtrsim$ 1 mag. We have developed techniques for fitting computed profiles to the low-J lines of H2, and thus determining column…

An unsupervised shape analysis is proposed to learn concepts reflecting shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constellations within objects is used in which constellations are…

Computer Vision and Pattern Recognition · Computer Science 2018-11-21 Christian A. Mueller , Andreas Birk

Column-density maps of molecular clouds are one of the most important observables in the context of molecular cloud- and star-formation (SF) studies. With the Herschel satellite it is now possible to determine the column density from dust…

Astrophysics of Galaxies · Physics 2015-03-04 N. Schneider , V. Ossenkopf , T. Csengeri , R. Klessen , C. Federrath , P. Tremblin , P. Girichidis , S. Bontemps , Ph. Andre

We compare velocity structure in the Polaris Flare molecular cloud at scales ranging from 0.015 pc to 20 pc to simulations of supersonic hydrodynamic and MHD turbulence computed with the ZEUS MHD code. We use several different statistical…

Astrophysics · Physics 2007-05-23 Volker Ossenkopf , Mordecai-Mark Mac Low

Understanding causal relationships among the variables of a system is paramount to explain and control its behavior. For many real-world systems, however, the true causal graph is not readily available and one must resort to predictions…

Machine Learning · Statistics 2024-12-20 Elias Eulig , Atalanti A. Mastakouri , Patrick Blöbaum , Michaela Hardt , Dominik Janzing

Persistent homology allows us to create topological summaries of complex data. In order to analyse these statistically, we need to choose a topological summary and a relevant metric space in which this topological summary exists. While…

Algebraic Topology · Mathematics 2019-06-24 Katharine Turner , Gard Spreemann

We employ the Delta-variance analysis and study the turbulent gas dynamics of simulated molecular clouds (MCs). Our models account for a simplified treatment of time-dependent chemistry and the non-isothermal nature of the gas. We…

Solar and Stellar Astrophysics · Physics 2015-08-06 Erik Bertram , Ralf S. Klessen , Simon C. O. Glover

Probability distribution functions (PDFs) of column densities are an established tool to characterize the evolutionary state of interstellar clouds. Using simulations, we show to what degree their determination is affected by noise,…

Instrumentation and Methods for Astrophysics · Physics 2016-05-25 Volker Ossenkopf-Okada , Timea Csengeri , Nicola Schneider , Christoph Federrath , Ralf S. Klessen

We propose the GraphSIM -- an objective metric to accurately predict the subjective quality of point cloud with superimposed geometry and color impairments. Motivated by the facts that human vision system is more sensitive to the high…

Image and Video Processing · Electrical Eng. & Systems 2020-12-23 Qi Yang , Zhan Ma , Yiling Xu , Zhu Li , Jun Sun

We show that specific higher dimensional shape information of point cloud data can be recovered by observing lower dimensional hierarchical clustering dynamics. We generate multiple point samples from point clouds and perform hierarchical…

Computational Geometry · Computer Science 2020-10-09 Paul Samuel P. Ignacio

Galaxy morphology reflects structural properties which contribute to understand the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented…

Astrophysics of Galaxies · Physics 2022-12-07 Shoulin Wei , Yadi Li , Wei Lu , Nan Li , Bo Liang , Wei Dai , Zhijian Zhang

Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…

Machine Learning · Computer Science 2020-01-14 Han Bao , Nam Dinh , Linyu Lin , Robert Youngblood , Jeffrey Lane , Hongbin Zhang

Collaborative intelligence is a new paradigm for efficient deployment of deep neural networks across the mobile-cloud infrastructure. By dividing the network between the mobile and the cloud, it is possible to distribute the computational…

Image and Video Processing · Electrical Eng. & Systems 2018-06-19 Hyomin Choi , Ivan V. Bajic

Galaxy morphology is a fundamental quantity, that is essential not only for the full spectrum of galaxy-evolution studies, but also for a plethora of science in observational cosmology. While a rich literature exists on…

Astrophysics of Galaxies · Physics 2020-01-08 Garreth Martin , Sugata Kaviraj , Alex Hocking , Shaun C. Read , James E. Geach

Efficiently processing structured point cloud data while preserving multiscale information is a key challenge across domains, from graphics to atomistic modeling. Using a curated dataset of simulated galaxy positions and properties,…

Machine Learning · Computer Science 2024-10-29 Julia Balla , Siddharth Mishra-Sharma , Carolina Cuesta-Lazaro , Tommi Jaakkola , Tess Smidt

We present the first study of the relationship between the column density distribution of molecular clouds within nearby Galactic spiral arms and their evolutionary status as measured from their stellar content. We analyze a sample of 195…

Astrophysics of Galaxies · Physics 2015-09-09 J. Abreu-Vicente , J. Kainulainen , A. Stutz , T. Henning , H. Beuther

The multi-scale nature of architectured materials raises the need for advanced experimental methods suitable for the identification of their effective properties, especially when their size is finite and they undergo extreme deformations.…

Applied Physics · Physics 2024-03-04 Filippo Agnelli , Pierre Margerit , Paolo Celli , Chiara Daraio , Andrei Constantinescu

We study the problem of two-sample comparison with categorical data when the contingency table is sparsely populated. In modern applications, the number of categories is often comparable to the sample size, causing existing methods to have…

Methodology · Statistics 2014-08-14 Hao Chen , Nancy R. Zhang