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In Lagrangian meshfree methods, the underlying spatial discretization, referred to as a point cloud or a particle cloud, moves with the flow velocity. In this paper, we consider different numerical methods of performing this movement of…

Numerical Analysis · Mathematics 2018-06-20 Pratik Suchde , Joerg Kuhnert

We design a monotone meshfree finite difference method for linear elliptic equations in the non-divergence form on point clouds via a nonlocal relaxation method. The key idea is a novel combination of a nonlocal integral relaxation of the…

Numerical Analysis · Mathematics 2023-08-08 Qihao Ye , Xiaochuan Tian

This paper investigates a discretization scheme for mean curvature motion on point cloud varifolds with particular emphasis on singular evolutions. To define the varifold a local covariance analysis is applied to compute an approximate…

Numerical Analysis · Mathematics 2020-10-20 Blanche Buet , Martin Rumpf

We present a mimetic finite-difference approach for solving Maxwell's equations in one and two spatial dimensions. After introducing the governing equations and the classical Finite-Difference Time-Domain (FDTD) method, we describe mimetic…

Numerical Analysis · Mathematics 2026-03-24 Johnny Corbino

We propose a novel framework to solve PDEs on moving manifolds, where the evolving surface is represented by a moving point cloud. This has the advantage of avoiding the need to discretize the bulk volume around the surface, while also…

Numerical Analysis · Mathematics 2019-06-20 Pratik Suchde , Joerg Kuhnert

It is currently difficult to distill discrete diffusion models. In contrast, continuous diffusion literature has many distillation approaches methods that can reduce sampling steps to a handful. Our method, Discrete Moment Matching…

Machine Learning · Computer Science 2026-03-23 Emiel Hoogeboom , David Ruhe , Jonathan Heek , Thomas Mensink , Tim Salimans

Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity local details, and are susceptible to error accumulation. To address this, we propose…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yichen Yang , Hong Li , Haodong Zhu , Linin Yang , Guojun Lei , Sheng Xu , Baochang Zhang

3D dynamic point clouds provide a natural discrete representation of real-world objects or scenes in motion, with a wide range of applications in immersive telepresence, autonomous driving, surveillance, \etc. Nevertheless, dynamic point…

Image and Video Processing · Electrical Eng. & Systems 2021-07-28 Wei Hu , Qianjiang Hu , Zehua Wang , Xiang Gao

In this paper, we present a powerful differentiable surface fitting technique to derive a compact surface representation for a given dense point cloud or mesh, with application in the domains of graphics and CAD/CAM. We have chosen the Loop…

Graphics · Computer Science 2022-10-20 Tianhao Xie

We present a novel Eulerian meshless method for two-phase flows with arbitrary embedded geometries. The spatial derivatives are computed using the meshless generalized finite difference method (GFDM). The sharp phase interface is tracked…

Fluid Dynamics · Physics 2024-06-27 Anand S Bharadwaj , Pratik Suchde , Prapanch Nair

Approximation of a target probability distribution using a finite set of points is a problem of fundamental importance in numerical integration. Several authors have proposed to select points by minimising a maximum mean discrepancy (MMD),…

Machine Learning · Statistics 2026-05-13 Zonghao Chen , Toni Karvonen , Heishiro Kanagawa , François-Xavier Briol , Chris. J. Oates

In this paper we apply the recently developed mimetic discretization method to the mixed formulation of the Stokes problem in terms of vorticity, velocity and pressure. The mimetic discretization presented in this paper and in [50] is a…

Numerical Analysis · Mathematics 2015-06-03 Jasper Kreeft , Marc Gerritsma

Recent advances in geometric deep-learning introduce complex computational challenges for evaluating the distance between meshes. From a mesh model, point clouds are necessary along with a robust distance metric to assess surface quality or…

Computer Vision and Pattern Recognition · Computer Science 2021-04-30 Léo Lebrat , Rodrigo Santa Cruz , Clinton Fookes , Olivier Salvado

We provide a comprehensive overview of meshfree collocation methods for numerically approximating differential operators on continuously labeled unstructured point clouds. Meshfree collocation methods do not require a computational grid or…

Numerical Analysis · Mathematics 2025-10-03 Tomas Halada , Serhii Yaskovets , Abhinav Singh , Ludek Benes , Pratik Suchde , Ivo F. Sbalzarini

We propose in this paper a discretization of the momentum convection operator for fluid flow simulations on quadrangular or hexahedral meshes. The space discretization is performed by the loworder nonconforming Rannacher-Turek finite…

Numerical Analysis · Mathematics 2023-01-06 Aubin Brunel , Raphaele Herbin , Jean-Claude Latché

Mesh-free numerical methods provide flexible discretisations for complex geometries; however, classical meshless discrete differential operators typically trade low computational cost for limited accuracy or high accuracy for substantial…

Machine Learning · Computer Science 2026-03-27 Lucas Gerken Starepravo , Georgios Fourtakas , Steven Lind , Ajay B. Harish , Tianning Tang , Jack R. C. King

In recent years, point cloud generation has gained significant attention in 3D generative modeling. Among existing approaches, point-based methods directly generate point clouds without relying on other representations such as latent…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Petr Molodyk , Jaemoo Choi , David W. Romero , Ming-Yu Liu , Yongxin Chen

We present and compare third- as well as fifth-order accurate finite difference schemes for the numerical solution of the compressible ideal MHD equations in multiple spatial dimensions. The selected methods lean on four different…

High Energy Astrophysical Phenomena · Physics 2015-05-18 A. Mignone , P. Tzeferacos , G. Bodo

Unsupervised point cloud segmentation is critical for embodied artificial intelligence and autonomous driving, as it mitigates the prohibitive cost of dense point-level annotations required by fully supervised methods. While integrating 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Yixiao Song , Qingyong Li , Wen Wang , Zhicheng Yan

A low-order mimetic finite difference (MFD) method for Reissner-Mindlin plate problems is considered. Together with the source problem, the free vibration and the buckling problems are investigated. Full details about the scheme…

Numerical Analysis · Mathematics 2012-07-10 Lourenco Beirao da Veiga , Carlo Lovadina , David Mora