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This paper presents theory for the Lagrange co-rotational (CR) formulation of finite elements in the geometrically nonlinear analysis of 3D structures. In this paper strains are assumed to be small while the magnitude of rotations from the…

Numerical Analysis · Mathematics 2013-04-29 Łukasz Kaczmarczyk , Tomasz Koziara , Chris J. Pearce

We prove in a very general framework several versions of the classical Poincar\'e-Birkhoff-Witt Theorem, which extend results from [BeGi, BrGa, CS, HvOZ, WW]. Applications and examples are discussed in the last part of the paper.

Quantum Algebra · Mathematics 2023-09-11 Alessandro Ardizzoni , Paolo Saracco , Dragoş Ştefan

We revise the classical continuum formulation behind the Spin Foam approach to the quantization of gravity. Based on the recent applications of the current EPRL-FK model beyond triangulations, we identify the tension with the implementation…

General Relativity and Quantum Cosmology · Physics 2018-11-15 Vadim Belov

We compute (algebraically) the Euler characteristic of a complex of sheaves with constructible cohomology. A stratified Poincar\'e-Hopf formula is then a consequence of the smooth Poincar\'e-Hopf theorem and of additivity of the…

Algebraic Topology · Mathematics 2009-05-29 Stéphane Simon

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

We introduce the notion of Q-filtrable varieties: projective varieties with a torus action and a finite number of fixed points, such that the cells of the associated Bialynicki-Birula decomposition are all rationally smooth. Our main…

Algebraic Geometry · Mathematics 2014-11-11 Richard Gonzales

In observational causal inference, in order to emulate a randomized experiment, weights are used to render treatments independent of observed covariates. This property is known as balance; in its absence, estimated causal effects may be…

Methodology · Statistics 2020-07-16 David Arbour , Drew Dimmery , Arjun Sondhi

In some applications of matching, the structural or hierarchical properties of the two graphs being aligned must be maintained. The hierarchical properties are induced by the direction of the edges in the two directed graphs. These…

Data Structures and Algorithms · Computer Science 2009-09-29 Sean M. Falconer , Dmitri Maslov

Gaussian graphical models typically assume a homogeneous structure across all subjects, which is often restrictive in applications. In this article, we propose a weighted pseudo-likelihood approach for graphical modeling which allows…

Methodology · Statistics 2023-03-17 Sutanoy Dasgupta , Peng Zhao , Jacob Helwig , Prasenjit Ghosh , Debdeep Pati , Bani K. Mallick

We give a brief exposition of the proof of the Cayley-Salmon theorem and its recent role in incidence geometry. Even when we don't use the properties of ruled surfaces explicitly, the regime in which we have interesting results in…

Combinatorics · Mathematics 2014-04-15 Nets Hawk Katz

A plethora of diverse aspect mechanisms exist today, all of which integrate concerns into artifacts that exhibit crosscutting structure. What we lack and need is a characterization of the design space that these aspect mechanisms inhabit…

Software Engineering · Computer Science 2007-05-23 Sergei Kojarski , David H. Lorenz

When a material surface is functionalized so as to acquire some type of order, functionalization of which soft condensed matter systems have recently provided many interesting examples, the modeller faces an alternative. Either the order is…

Soft Condensed Matter · Physics 2018-07-25 Leonid V. Mirantsev , André M. Sonnet , Epifanio G. Virga

In earlier work, we constructed invariants of irreducible representations of the Kauffman skein algebra of a surface. We introduce here an inverse construction, which to a set of possible invariants associates an irreducible representation…

Geometric Topology · Mathematics 2018-03-16 Francis Bonahon , Helen Wong

Envelope methodology is succinctly pitched as a class of procedures for increasing efficiency in multivariate analyses without altering traditional objectives \citep[first sentence of page 1]{cook2018introduction}. This description is true…

Methodology · Statistics 2020-02-05 Daniel J. Eck

Model merging, particularly through weight averaging, has shown surprising effectiveness in saving computations and improving model performance without any additional training. However, the interpretability of why and how this technique…

Machine Learning · Computer Science 2025-08-20 Hu Wang , Congbo Ma , Ibrahim Almakky , Ian Reid , Gustavo Carneiro , Mohammad Yaqub

A model for cross-over designs with repeated measures within each period was developed. It is obtained using an extension of generalized estimating equations that includes a parametric component to model treatment effects and a…

Methodology · Statistics 2023-03-21 N. A. Cruz , O. O. Melo , C. A. Martinez

The factor modeling for high-dimensional time series is powerful in discovering latent common components for dimension reduction and information extraction. Most available estimation methods can be divided into two categories: the…

Methodology · Statistics 2026-05-26 Xinghao Qiao , Zihan Wang , Qiwei Yao , Bo Zhang

In this paper we address the issue of designing developable surfaces with Bezier patches. We show that developable surfaces with a polynomial edge of regression are the set of developable surfaces which can be constructed with Aumann's…

Graphics · Computer Science 2017-06-19 L. Fernández-Jambrina

In this article, we propose a modified convex combination of the polynomial reconstructions of odd-order WENO schemes to maintain the central substencil prevalence over the lateral ones in all parts of the solution. New "centered" versions…

Numerical Analysis · Mathematics 2023-11-17 Daniel Barreto , Rafael B. de R. Borges , Bruno Costa , Silvaneo dos Santos

Linearization of attention using various kernel approximation and kernel learning techniques has shown promise. Past methods used a subset of combinations of component functions and weight matrices within the random feature paradigm. We…

Machine Learning · Computer Science 2025-09-24 Duke Nguyen , Du Yin , Aditya Joshi , Flora Salim