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3D point cloud semantic segmentation is one of the fundamental tasks for environmental understanding. Although significant progress has been made in recent years, the performance of classes with few examples or few points is still far from…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Shoumeng Qiu , Feng Jiang , Haiqiang Zhang , Xiangyang Xue , Jian Pu

The purpose of this paper is to study stochastic evolution inclusions of the form \begin{align*} \eta(t,z) N_{\Theta}(dt \otimes z)\in dX(t)+\mathcal{A} X(t)dt, \end{align*} where $\mathcal{A}$ is a multi-valued operator acting on a…

Probability · Mathematics 2017-10-06 Alexander Nerlich

The randomized singular value decomposition proposed in [27] has certainly become one of the most well-established randomization-based algorithms in numerical linear algebra. The key ingredient of the entire procedure is the computation of…

Numerical Analysis · Mathematics 2025-08-01 Davide Palitta , Sascha Portaro

The spectral energy distribution (SED) of observed stars in wide-field images is crucial for chromatic point spread function (PSF) modelling methods, which use unresolved stars as integrated spectral samples of the PSF across the field of…

Instrumentation and Methods for Astrophysics · Physics 2025-02-19 Ezequiel Centofanti , Samuel Farrens , Jean-Luc Starck , Tobias Liaudat , Alex Szapiro , Jennifer Pollack

Learning and analyzing 3D point clouds with deep networks is challenging due to the sparseness and irregularity of the data. In this paper, we present a data-driven point cloud upsampling technique. The key idea is to learn multi-level…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Lequan Yu , Xianzhi Li , Chi-Wing Fu , Daniel Cohen-Or , Pheng-Ann Heng

Bayesian change-point detection, together with latent variable models, allows to perform segmentation over high-dimensional time-series. We assume that change-points lie on a lower-dimensional manifold where we aim to infer subsets of…

Machine Learning · Statistics 2020-11-04 Lorena Romero-Medrano , Pablo Moreno-Muñoz , Antonio Artés-Rodríguez

The wave equation for vectors and symmetric tensors in spherical coordinates is studied under the divergence-free constraint. We describe a numerical method, based on the spectral decomposition of vector/tensor components onto spherical…

General Relativity and Quantum Cosmology · Physics 2009-11-23 Jerome Novak , Jean-Louis Cornou , Nicolas Vasset

We propose a single time-scale stochastic subgradient method for constrained optimization of a composition of several nonsmooth and nonconvex functions. The functions are assumed to be locally Lipschitz and differentiable in a generalized…

Optimization and Control · Mathematics 2020-12-22 Andrzej Ruszczynski

A particle method for reproducing the phase space of collisionless stellar systems is described. The key idea originates in Liouville's theorem which states that the distribution function (DF) at time t can be derived from tracing necessary…

Astrophysics · Physics 2009-10-30 Shunsuke Hozumi

The Phase-Space approach (PSA), which was originally introduced in [Lacroix et al., Phys. Rev. D 106, 123006 (2022)] to describe neutrino flavor oscillations for interacting neutrinos emitted from stellar objects is extended to describe…

High Energy Physics - Phenomenology · Physics 2024-10-29 Denis Lacroix , Angel Bauge , Bulent Yilmaz , Mariane Mangin-Brinet , Alessandro Roggero , A. Baha Balantekin

Anomalous diffusion in the presence or absence of an external force field is often modelled in terms of the fractional evolution equations, which can involve the hyper-singular source term. For this case, conventional time stepping methods…

Numerical Analysis · Mathematics 2023-09-19 Jiankang Shi , Minghua Chen , Jianxiong Cao

We present first results from a new parton shower event generator, Deductor. Anticipating a need for an improved treatment of parton color and spin, the structure of the generator is based on the quantum density matrix in color and spin…

High Energy Physics - Phenomenology · Physics 2015-06-18 Zoltan Nagy , Davison E. Soper

We present a new class of particle methods with deformable shapes that converge in the uniform norm without requiring remappings, extended overlapping or vanishing moments for the particles. The crux of the method is to use polynomial…

Numerical Analysis · Mathematics 2013-08-02 Martin Campos Pinto

Solutions to fractional models inherently exhibit non-smooth behavior, which significantly deteriorates the accuracy and therefore efficiency of existing numerical methods. We develop a two-stage data-infused computational framework for…

Numerical Analysis · Mathematics 2018-10-30 Jorge L. Suzuki , Mohsen Zayernouri

Spatial point process (SPP) models are commonly used to analyze point pattern data in many fields, including presence-only data in ecology. Existing exact Bayesian methods for fitting these models are computationally expensive because they…

This paper presents an efficient automatic color image segmentation method using a seeded region growing and merging method based on square elemental regions. Our segmentation method consists of the three steps: generating seed regions,…

Computer Vision and Pattern Recognition · Computer Science 2017-11-28 Hisashi Shimodaira

The paper studies processes defined on time domains structured as oriented spatial graphs (or metric graphs, or oriented branched 1-manifolds). This setting can be used, for example, for forecasting models involving branching scenarios. For…

Information Theory · Computer Science 2022-05-13 Nikolai Dokuchaev

When the initial state evolution of a parton shower is organized according to the standard "backward evolution'' prescription, ratios of parton distribution functions appear in the splitting probabilities. The shower thus organized evolves…

High Energy Physics - Phenomenology · Physics 2015-06-18 Zoltan Nagy , Davison E. Soper

We propose a new smoothing method for obtaining surface densities from discrete particle positions from numerical simulations. This is an essential step for many applications in gravitational lensing. This method is based on the ``scatter''…

Astrophysics · Physics 2011-02-11 Guo-Liang Li , S. Mao , Y. P. Jing , X. Kang , M. Bartelmann

The fundamental aim of clustering algorithms is to partition data points. We consider tasks where the discovered partition is allowed to vary with some covariate such as space or time. One approach would be to use fragmentation-coagulation…

Machine Learning · Statistics 2013-11-01 Konstantina Palla , David A. Knowles , Zoubin Ghahramani
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