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No generic function for the minicolumn, i.e., one that would apply equally well to all cortical areas and species, has yet been proposed. I propose that the minicolumn does have a generic functionality, which only becomes clear when seen in…

Neurons and Cognition · Quantitative Biology 2017-07-14 Gerard J. Rinkus

Unsupervised image segmentation aims at clustering the set of pixels of an image into spatially homogeneous regions. We introduce here a class of Bayesian nonparametric models to address this problem. These models are based on a combination…

Machine Learning · Statistics 2016-02-10 Richard Yi Da Xu , Francois Caron , Arnaud Doucet

Cell segmentation is a fundamental task in microscopy image analysis. Several foundation models for cell segmentation have been introduced, virtually all of them are extensions of Segment Anything Model (SAM), improving it for microscopy…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Anwai Archit , Constantin Pape

We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical…

Statistical Mechanics · Physics 2017-09-13 Lester O. Hedges , H. Alicia Kim , Robert L. Jack

Vision foundation models (FMs) are accelerating the development of digital pathology algorithms and transforming biomedical research. These models learn, in a self-supervised manner, to represent histological features in highly…

Statisticians increasingly face the problem to reconsider the adaptability of classical inference techniques. In particular, divers types of high-dimensional data structures are observed in various research areas; disclosing the boundaries…

Statistics Theory · Mathematics 2017-06-09 Paavo Sattler , Markus Pauly

This paper proposes a concise coding of the cells of n-dimensional finite regular grids. It induces a simple, generic and efficient framework for implementing classical digital topology data structures and algorithms. Discrete subsets of…

Discrete Mathematics · Computer Science 2009-06-16 Jacques-Olivier Lachaud

System-level design, once the province of board designers, has now become a central concern for chip designers. Because chip design is a less forgiving design medium -- design cycles are longer and mistakes are harder to correct --…

Hardware Architecture · Computer Science 2025-07-15 Shuvra S. Bhattacharyya , Marilyn Wolf

In this paper, a parametric level set method for reconstruction of obstacles in general inverse problems is considered. General evolution equations for the reconstruction of unknown obstacles are derived in terms of the underlying level set…

Analysis of PDEs · Mathematics 2011-10-07 Alireza Aghasi , Misha Kilmer , Eric L. Miller

Metasurfaces, with their superior capability in manipulating the optical wavefront at the subwavelength scale and low manufacturing complexity, have shown great potential for planar photonics and novel optical devices. However, vector field…

Optics · Physics 2016-04-20 Weimin Ye , Qinghua Guo , Yuanjiang Xiang , Dianyuan Fan , Shuang Zhang

We address 2D floorplan reconstruction from 3D scans. Existing approaches typically employ heuristically designed multi-stage pipelines. Instead, we formulate floorplan reconstruction as a single-stage structured prediction task: find a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Yuanwen Yue , Theodora Kontogianni , Konrad Schindler , Francis Engelmann

We present a general method to obtain interesting subspaces of the $C^2$ cubic spline space defined on the cubic Wang-Shi refinement of a given arbitrary triangulation $\mathcal{T}$. These subspaces are characterized by specific Hermite…

Numerical Analysis · Mathematics 2024-12-25 Tom Lyche , Carla Manni , Hendrik Speleers

A long-standing challenge is designing multi-scale structures with good connectivity between cells while optimizing each cell to reach close to the theoretical performance limit. We propose a new method for direct multi-scale topology…

Neural and Evolutionary Computing · Computer Science 2025-02-21 Hongrui Chen , Xingchen Liu , Levent Burak Kara

Seamless global parametrization of surfaces is a key operation in geometry processing, e.g. for high-quality quad mesh generation. A common approach is to prescribe the parametric domain structure, in particular the locations of…

Graphics · Computer Science 2021-04-13 Marcel Campen , Hanxiao Shen , Jiaran Zhou , Denis Zorin

A multiscale (micro-to-macro) analysis is proposed for the prediction of the finite strain behavior of composites with hyperelastic constituents and embedded localized damage. The composites are assumed to possess periodic microstructure…

Materials Science · Physics 2020-10-20 Nathan Perchikov , Jacob Aboudi

The optimization along the chain processing-structure-properties-performance is one of the core objectives in data-driven materials science. In this sense, processes are supposed to manufacture workpieces with targeted material…

Materials Science · Physics 2022-03-24 Tarek Iraki , Lukas Morand , Johannes Dornheim , Norbert Link , Dirk Helm

Jeandel and Rao proved that 11 is the size of the smallest set of Wang tiles, i.e., unit squares with colored edges, that admit valid tilings (contiguous edges of adjacent tiles have the same color) of the plane, none of them being…

Dynamical Systems · Mathematics 2021-05-27 Sébastien Labbé

In this paper, we propose oversampling strategies in the Generalized Multiscale Finite Element Method (GMsFEM) framework. The GMsFEM, which has been recently introduced in [12], allows solving multiscale parameter-dependent problems at a…

Analysis of PDEs · Mathematics 2013-04-18 Yalchin Efendiev , Juan Galvis , Guanglian Li , Michael Presho

Accelerating materials development requires quantitative linkages between processing, microstructure, and properties. In this work, we introduce a framework for mapping microstructure onto a low-dimensional material manifold that is…

Materials Science · Physics 2026-05-20 Simon A. Mason , Megna N. Shah , Jeffrey P. Simmons , Dennis M. Dimiduk , Stephen R. Niezgoda

Density Functional Theory (DFT) has become the quasi-standard for ab-initio simulations for a wide range of applications. While the intrinsic cubic scaling of DFT was for a long time limiting the accessible system size to some hundred…

Materials Science · Physics 2018-02-23 Stephan Mohr , Marc Eixarch , Maximilian Amsler , Mervi J. Mantsinen , Luigi Genovese