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This paper introduces Bounded Fuzzy Possibilistic Method (BFPM) by addressing several issues that previous clustering/classification methods have not considered. In fuzzy clustering, object's membership values should sum to 1. Hence, any…

Machine Learning · Computer Science 2019-02-11 Hossein Yazdani

In this paper we define novel topological invariants of doubly periodic tangles (DP tangles). DP tangles are embeddings of curves in the thickened plane with translational symmetries in two independent directions. We first organize the…

Geometric Topology · Mathematics 2024-08-30 Ioannis Diamantis , Sofia Lambropoulou , Sonia Mahmoudi

In this paper, notion of p - norm generalized trapezoidal intuitionistic fuzzy numbers is introduced. A new ranking method is introduced for p - norm generalized trapezoidal intuitionistic fuzzy numbers. Also we consider linear programming…

Optimization and Control · Mathematics 2015-12-08 Shashi Aggarwal , Chavi Gupta

Point normal, as an intrinsic geometric property of 3D objects, not only serves conventional geometric tasks such as surface consolidation and reconstruction, but also facilitates cutting-edge learning-based techniques for shape analysis…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Haoran Zhou , Honghua Chen , Yingkui Zhang , Mingqiang Wei , Haoran Xie , Jun Wang , Tong Lu , Jing Qin , Xiao-Ping Zhang

Image-to-point cloud (I2P) registration is a fundamental task for robots and autonomous vehicles to achieve cross-modality data fusion and localization. Current I2P registration methods primarily focus on estimating correspondences at the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Shuhao Kang , Youqi Liao , Jianping Li , Fuxun Liang , Yuhao Li , Xianghong Zou , Fangning Li , Xieyuanli Chen , Zhen Dong , Bisheng Yang

Researches in granular modeling produced a variety of mathematical models, such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules. Modeling of…

Artificial Intelligence · Computer Science 2015-04-30 Lorenzo Livi , Alireza Sadeghian

A data-driven model identification strategy is developed for dynamical systems near a supercritical Hopf bifurcation with nonautonomous inputs. This strategy draws on phase-amplitude reduction techniques, leveraging an analytical…

Dynamical Systems · Mathematics 2024-05-07 Dan Wilson

We construct various exact analytical solutions of the $SO(3)$ BMN matrix model that correspond to rotating fuzzy spheres and rotating fuzzy tori.These are also solutions of Yang Mills theory compactified on a sphere times time and they are…

High Energy Physics - Theory · Physics 2015-06-16 David Berenstein , Eric Dzienkowski , Robin Lashof-Regas

Any order generation of discrete data using masked diffusion models (MDMs) offers a compelling alternative to traditional autoregressive models, especially in domains that lack a natural causal ordering of data. However, current popular…

We investigate spherically-symmetric, general relativistic systems of collapsing perfect fluid distributions. We consider neutron star models that are driven to collapse by the addition of an initially "in-going" velocity profile to the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Scott C. Noble , Matthew W. Choptuik

We argue supersymmetric generalizations of fuzzy two- and four-spheres based on the unitary-orthosymplectic algebras, $uosp(N|2)$ and $uosp(N|4)$, respectively. Supersymmetric version of Schwinger construction is applied to derive graded…

High Energy Physics - Theory · Physics 2015-05-28 Kazuki Hasebe

Data reduction techniques published so far for the CoRoT N2 data product were targeted primarily on the detection of extrasolar planets. Since the whole dataset has been released, specific algorithms are required to process the lightcurves…

Instrumentation and Methods for Astrophysics · Physics 2015-03-20 Joerg Weingrill

Approaches based on computing with words find good applicability in decision making systems. Predominantly finding their basis in type-1 fuzzy sets, computing with words approaches employ type-1 fuzzy sets as semantics of the linguistic…

Artificial Intelligence · Computer Science 2020-02-28 Taniya Seth , Pranab K. Muhuri

The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-clustering algorithms for…

Machine Learning · Computer Science 2023-02-06 Kaijie Xu

Two-phase random textures abound in a host of contexts, porous and composite media, ecological structures, biological media and astrophysical structures. Questions surrounding the spatial structure of such textures continue to pose many…

Materials Science · Physics 2012-01-04 Yang Jiao , Sal Torquato , Frank H. Stillinger

Normalizing flows have shown great promise for modelling flexible probability distributions in a computationally tractable way. However, whilst data is often naturally described on Riemannian manifolds such as spheres, torii, and hyperbolic…

Machine Learning · Statistics 2020-12-10 Emile Mathieu , Maximilian Nickel

Modern shape design and capture techniques often lead to the geometric data presented in the form of serial rows of data points. In general, the number of data points varies from row to row. Lofted or skinned B-spline surface interpolation…

Graphics · Computer Science 2022-02-15 Shutao Tang

We study a model of Tensorial Group Field Theory (TGFT) on $\mathbb{R}^3$ from the point of view of the Functional Renormalisation Group. This is the first attempt to apply a renormalisation procedure to a TGFT model defined over a…

High Energy Physics - Theory · Physics 2015-12-09 Joseph Ben Geloun , Riccardo Martini , Daniele Oriti

We construct (2+1)-dimensional lattice systems, which we call fusion surface models. These models have finite non-invertible symmetries described by general fusion 2-categories. Our method can be applied to build microscopic models with,…

Strongly Correlated Electrons · Physics 2024-06-05 Kansei Inamura , Kantaro Ohmori

Point clouds are characterized by irregularity and unstructuredness, which pose challenges in efficient data exploitation and discriminative feature extraction. In this paper, we present an unsupervised deep neural architecture called…

Computer Vision and Pattern Recognition · Computer Science 2023-02-08 Qijian Zhang , Junhui Hou , Yue Qian , Yiming Zeng , Juyong Zhang , Ying He