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Clustering, as an unsupervised technique, plays a pivotal role in various data analysis applications. Among clustering algorithms, Spectral Clustering on Euclidean Spaces has been extensively studied. However, with the rapid evolution of…

Machine Learning · Computer Science 2024-12-09 Sagar Ghosh , Swagatam Das

Cryo-electron microscopy (cryo-EM), the subject of the 2017 Nobel Prize in Chemistry, is a technology for determining the 3-D structure of macromolecules from many noisy 2-D projections of instances of these macromolecules, whose…

Computer Vision and Pattern Recognition · Computer Science 2020-04-22 Roy R. Lederman , Joakim Andén , Amit Singer

Medical anomaly detection has emerged as a promising solution to challenges in data availability and labeling constraints. Traditional methods extract features from different layers of pre-trained networks in Euclidean space; however,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Alvaro Gonzalez-Jimenez , Simone Lionetti , Ludovic Amruthalingam , Philippe Gottfrois , Fabian Gröger , Marc Pouly , Alexander A. Navarini

Phoretic colloids self-propel thanks to surface flows generated in response to surface gradients (thermal, electrical, or chemical), that are self-induced and/or generated by other particles. Here we present a scalable and versatile…

Soft Condensed Matter · Physics 2024-07-29 Blaise Delmotte , Florencio Balboa Usabiaga

Parametrized families of PDEs arise in various contexts such as inverse problems, control and optimization, risk assessment, and uncertainty quantification. In most of these applications, the number of parameters is large or perhaps even…

Analysis of PDEs · Mathematics 2015-03-04 Albert Cohen , Ronald Devore

In this article, via certain lower bound conditions on the measures under consideration, the authors fully characterize the Sobolev embeddings for the scales of Haj{\l}asz-Triebel-Lizorkin and Haj{\l}asz-Besov spaces in the general context…

Functional Analysis · Mathematics 2022-02-15 Ryan Alvarado , Dachun Yang , Wen Yuan

The hyperbolic manifold is a smooth manifold of negative constant curvature. While the hyperbolic manifold is well-studied in the literature, it has gained interest in the machine learning and natural language processing communities lately…

Machine Learning · Computer Science 2019-03-19 Pratik Jawanpuria , Mayank Meghwanshi , Bamdev Mishra

Electrolyte solutions play critical role in a vast range of important applications, yet an accurate and scalable method of predicting their properties without fitting to experiment has remained out of reach, despite over a century of…

Chemical Physics · Physics 2024-11-18 Junji Zhang , Joshua Pagotto , Tim Gould , Timothy T. Duignan

Implicit schemes are popular methods for the integration of time dependent PDEs such as hyperbolic and parabolic PDEs. However the necessity to solve corresponding linear systems at each time step constitutes a complexity bottleneck in…

Numerical Analysis · Mathematics 2018-06-14 Houman Owhadi , Lei Zhang

We prove a Morse Lemma for coarsely regular quasigeodesics in nonpositively curved symmetric spaces and euclidean buildings X. The main application is a simpler coarse geometric characterization of Morse subgroups of the isometry groups…

Group Theory · Mathematics 2018-12-19 Michael Kapovich , Bernhard Leeb , Joan Porti

The parametrization theorem is derived in a flat nD pseudo-complex affine space. The pseudo-complex hyperbolic space accomodates n-number of uncompactified time-like extra dimensions with sugnature (s,r), where s and r are the numbers of…

Differential Geometry · Mathematics 2010-03-02 Minh Q. Truong

We investigate computational issues in the distributed model Amoebots of programmable matter. In this model, the computational entities, called particles, are anonymous finite-state machines that operate and move on an hexagonal tasselation…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-01 Giuseppe Antonio Di Luna , Paola Flocchini , Nicola Santoro , Giovanni Viglietta , Yukiko Yamauchi

The degenerate singularities of systems from one well-known multiparameter family of integrable systems of rigid body dynamics are studied. Axisymmetric Zhukovsky systems are considered, i.e. axisymmetric Euler tops after adding a constant…

Dynamical Systems · Mathematics 2021-11-08 Vladislav Kibkalo

In this paper, we present an image separation method for separating images into point- and curvelike parts by employing a combined dictionary consisting of wavelets and compactly supported shearlets utilizing the fact that they sparsely…

Numerical Analysis · Mathematics 2011-06-13 Gitta Kutyniok , Wang-Q Lim

When analyzing parametric statistical models, a useful approach consists in modeling geometrically the parameter space. However, even for very simple and commonly used hierarchical models like statistical mixtures or stochastic deep neural…

Machine Learning · Computer Science 2021-12-08 Pascal Mattia Esser , Frank Nielsen

We derive a hyperbolic system of equations approximating the two-layer dispersive shallow water model for shear flows recently proposed by Gavrilyuk, Liapidevskii \& Chesnokov (J. Fluid Mech., vol. 808, 2016, pp. 441--468). The use of this…

Fluid Dynamics · Physics 2019-05-02 Alexander Chesnokov , Trieu Nguyen

Microscopy research often requires recovering particle-size distributions in three dimensions from only a few (10 - 200) profile measurements in the section. This problem is especially relevant for petrographic and mineralogical studies,…

Methodology · Statistics 2022-02-16 Ekaterina Poliakova

A new development of the ``monodromy transform'' method for analysis of hyperbolic as well as elliptic integrable reductions of Einstein equations is presented. Compatibility conditions for some alternative representations of the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 G. A. Alekseev

Hyperbolic geometry has emerged as an effective latent space for representing complex networks, owing to its ability to capture hierarchical organization and heterogeneous connectivity patterns using low-dimensional embeddings. As a result,…

Machine Learning · Computer Science 2026-05-01 Sofía Pérez Casulo , Marcelo Fiori , Bernardo Marenco , Federico Larroca

Systems of particles interacting via inverse-power law potentials have an invariance with respect to changes in length and temperature, implying a correspondence in the dynamics and thermodynamics between different `isomorphic' sets of…

Statistical Mechanics · Physics 2016-08-03 Thibaud Maimbourg , Jorge Kurchan