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Deep learning applied to the reconstruction of 3D shapes has seen growing interest. A popular approach to 3D reconstruction and generation in recent years has been the CNN encoder-decoder model usually applied in voxel space. However, this…

Computer Vision and Pattern Recognition · Computer Science 2020-05-12 Mateusz Michalkiewicz , Eugene Belilovsky , Mahsa Baktashmotlagh , Anders Eriksson

This paper presents a phase-field model for simulating the three-dimensional deformation of vesicle membranes, incorporating area-difference elasticity, with constraints on bulk volume and surface area. We develop efficient numerical…

Numerical Analysis · Mathematics 2025-11-19 Yihong Liang , Emine Celiker , Ping Lin

Shape retrieval and alignment are a promising avenue towards turning 3D scans into lightweight CAD representations that can be used for content creation such as mobile or AR/VR gaming scenarios. Unfortunately, CAD model retrieval is limited…

Computer Vision and Pattern Recognition · Computer Science 2020-07-24 Vladislav Ishimtsev , Alexey Bokhovkin , Alexey Artemov , Savva Ignatyev , Matthias Niessner , Denis Zorin , Evgeny Burnaev

Multi-degree splines are piecewise polynomial functions having sections of different degrees. For these splines, we discuss the construction of a B-spline basis by means of integral recurrence relations, extending the class of multi-degree…

Numerical Analysis · Mathematics 2017-09-18 Carolina Vittoria Beccari , Giulio Casciola , Serena Morigi

The emergence of multicellularity and developmental programs are among the major problems of evolutionary biology. Traditionally, research in this area has been based on the combination of data analysis and experimental work on one hand and…

Populations and Evolution · Quantitative Biology 2014-03-14 Ricard V. Solé , Salva Duran-Nebreda

In this work, we investigate probe scalar field models preserving covariance on fixed, static background geometries that present hyperscaling violation properties. We develop a first-order framework that rises from restrictions on the…

High Energy Physics - Theory · Physics 2024-06-13 I. Andrade , M. A. Marques , R. Menezes , D. C. Moreira

This paper presents a novel approach to reconstruct complete 3D deformable models over time by a single depth camera. These are the steps employed for deforming objects from single depth camera. The partial surfaces reconstructed from…

Computer Vision and Pattern Recognition · Computer Science 2017-08-31 Vamshhi Pavan Kumar Varma Vegeshna

Missing data is a significant problem impacting all domains. State-of-the-art framework for minimizing missing data bias is multiple imputation, for which the choice of an imputation model remains nontrivial. We propose a multiple…

Machine Learning · Computer Science 2018-02-20 Lovedeep Gondara , Ke Wang

This contribution presents a diffuse framework for modeling cracks in heterogeneous media. Interfaces are depicted by static phase-fields. This concept allows the use of non-conforming meshes. Another phase-field is used to describe the…

Materials Science · Physics 2020-05-11 Arne Claus Hansen-Dörr , Franz Dammaß , René de Borst , Markus Kästner

We study perturbations of linear differential equations, deriving explicit series solutions, using Dyson-type expansions. We analyze the monodromy of deformed solutions in a number of examples, and relate this to cocycles in a cohomological…

Classical Analysis and ODEs · Mathematics 2025-09-04 Ziyu Zhang

In material science, models are derived to predict emergent material properties (e.g. elasticity, strength, conductivity) and their relations to processing conditions. A major drawback is the calibration of model parameters that depend on…

Neural and Evolutionary Computing · Computer Science 2021-11-22 Gabriel Kronberger , Evgeniya Kabliman , Johannes Kronsteiner , Michael Kommenda

The continuum mechanics of line defects representing singularities due to terminating discontinuities of the elastic displacement and its gradient field is developed. The development is intended for application to coupled phase…

Materials Science · Physics 2016-03-09 Amit Acharya , Claude Fressenegeas

We compute the influence action for a system perturbatively coupled to a linear scalar field acting as the environment. Subtleties related to divergences that appear when summing over all the modes are made explicit and clarified. Being…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Albert Roura , Enric Verdaguer

We describe a framework for reformulating and solving optimization problems that generalizes the well-known framework originally introduced by Benders. We discuss details of the application of the procedures to several classes of…

Optimization and Control · Mathematics 2023-07-14 Suresh Bolusani , Ted K. Ralphs

In many applied sciences a popular analysis strategy for high-dimensional data is to fit many multivariate generalized linear models in parallel. This paper presents a novel approach to address the resulting multiple testing problem by…

Statistics Theory · Mathematics 2024-10-07 Riccardo De Santis , Jelle J. Goeman , Samuel Davenport , Jesse Hemerik , Livio Finos

In this paper, we study a hydrodynamic phase-field system modeling the deformation of functionalized membranes in incompressible viscous fluids. The governing PDE system consists of the Navier-Stokes equations coupled with a convective…

Analysis of PDEs · Mathematics 2022-06-22 Hao Wu , Yuchen Yang

The output of molecular dynamics simulations is high-dimensional, and the degrees of freedom among the atoms are related in intricate ways. Therefore, a variety of analysis frameworks have been introduced in order to distill complex motions…

Biomolecules · Quantitative Biology 2019-08-06 Brooke E. Husic , Frank Noé

This paper presents an overview of the theories and computer implementation aspects of phase field models (PFM) of fracture. The advantage of PFM over discontinuous approaches to fracture is that PFM can elegantly simulate complicated…

Geophysics · Physics 2023-09-11 X. Zhuang , S. Zhou , G. D. Huynh , P. Areias , T. Rabczuk

We present a new deep learning approach for matching deformable shapes by introducing {\it Shape Deformation Networks} which jointly encode 3D shapes and correspondences. This is achieved by factoring the surface representation into (i) a…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Thibault Groueix , Matthew Fisher , Vladimir G. Kim , Bryan C. Russell , Mathieu Aubry

The decoupling of multivariate functions is a powerful modeling paradigm for learning multivariate input-output relations from data. For the single-layer case, established CPD-based methods are available, but the multi-layer case remained…

Systems and Control · Electrical Eng. & Systems 2026-04-14 Joppe De Jonghe , Konstantin Usevich , Philippe Dreesen , Mariya Ishteva
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