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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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121243364485 · May 202619922001200920172026
48 results for elastic structures

In non-linear incompatible elasticity, the configurations are maps from a non-Euclidean body manifold into the ambient Euclidean space, Rk\mathbb{R}^k. We prove the ΓΓ-convergence of elastic energies for configurations of a converging sequence, MnM\mathcal{M}_n\to\mathcal{M}, of body manifolds. This convergence result …

2015-11-07abs ↗pdf ↗

New methods for estimating and inferring nonparametric structural functions and elasticities.

problem Estimating and inferring nonparametric structural functions and their derivatives.
method Data-driven sieve dimension choice and uniform confidence bands construction.
result Optimal estimation and inference procedures with minimax rates of convergence.

Estimates price elasticity from autocorrelated time series using causal graphs.

problem Inconsistent IV estimators in autocorrelated time series data.
method Model equilibrium with unobserved confounders, derive DAG, and use graphical inference for valid IV estimators.
result Valid IV estimators improve understanding of economic dynamics.

Classical elasticity is concerned with bodies that can be modeled as smooth manifolds endowed with a reference metric that represents local equilibrium distances between neighboring material elements. The elastic energy associated with a configuration of a body in classical elasticity is the sum of local contributions …

2013-06-07abs ↗pdf ↗

The paper studies rigidity and continuity in nonlinear elasticity on manifolds and hypersurfaces.

problem Rigidity and continuity properties of elastic bodies in non-Euclidean settings.
method Geometric rigidity estimates, asymptotic rigidity of elastic membranes, simplified geometric proof of continuous dependence.
result Established geometric rigidity estimate and proved asymptotic rigidity of elastic membranes.

Study preserves planar and graphical properties of curves under elastic flow.

problem Maintaining planar and graphical properties of non-compact curves under elastic flow.
method Extended recent work on adapted elastic energy to derive thresholds for planar and graphical embeddedness.
result Derived new Li--Yau type inequality for complete planar curves.

The paper studies the free elastic flow of closed curves and finds their asymptotic shape converges to a circle.

problem Challenges in studying the asymptotic behavior of the free elastic flow for closed curves.
method Analysis of the free elastic flow as an L2L^2-gradient flow for Euler's elastic energy.
result An appropriate rescaling of initial curves geometrically close to circles converges to a unique round circle.

Motivated by the problem of finding an explicit description of a developable narrow Moebius strip of minimal bending energy, which was first formulated by M. Sadowsky in 1930, we will develop the theory of elastic strips. Recently E.L. Starostin and G.H.M. van der Heijden found a numerical description for an elastic Mo…

2010-01-22abs ↗pdf ↗

Study gauge freedoms in elastic wave equations and Dirichlet-to-Neumann map.

problem Recover stiffness tensor and density from Dirichlet-to-Neumann map.
method Analyze invariance under coordinate transformations and gauge freedoms.
result Present gauge freedoms in the Dirichlet-to-Neumann map for Riemannian elastic wave equation.

Study models deep learning training dynamics using locally elastic SDEs to reveal feature separability.

problem Understanding how deep learning models separate features from different classes during training.
method Modeling deep learning training using locally elastic SDEs with a drift term reflecting backpropagation impact.
result Local elasticity in SDEs leads to linear separability of features, resulting in vanishing training loss.

Multiple kernel learning (MKL), structured sparsity, and multi-task learning have recently received considerable attention. In this paper, we show how different MKL algorithms can be understood as applications of either regularization on the kernel weights or block-norm-based regularization, which is more common in str…

2010-11-13abs ↗pdf ↗

We study a class of elastic energy functionals for maps between planar domains (among them the so-called squared distance functional) whose critical points (elastic maps) allow a far more complete theory than one would expect from general elasticity theory. For some of these functionals elastic maps even admit a "Weier…

2017-06-20abs ↗pdf ↗

Study of elastic models in non-Euclidean spaces via Γ-convergence.

problem Elasticity in non-Euclidean ambient spaces with incompatible local rest distances.
method Γ-convergence to derive a limit elastic model, relating minimum energy to curvature discrepancy.
result Linearized version of a conjecture in elasticity confirmed, linking energy to curvature.

New discrete curves defined in space forms with geometric properties.

problem Defining discrete elastic and constrained elastic curves in space forms.
method Extending discrete Euclidean curvature to space forms and using Bäcklund transformations.
result Discrete elastic and constrained elastic curves are elements of a curve hierarchy.

Structure learning in random fields has attracted considerable attention due to its difficulty and importance in areas such as remote sensing, computational biology, natural language processing, protein networks, and social network analysis. We consider the problem of estimating the probabilistic graph structure associ…

2011-11-02abs ↗pdf ↗

A geometrical interpretation of the GG-structures associated to elastic material bodies is given. In addition, characterizations of their integrability are obtained. Since the lack of integrability is a geometrical measure of the lack of homogeneity, the corresponding inhomogeneity conditions are obtained

2004-01-28abs ↗pdf ↗

Demand variance can result in a mismatch between planned supply and actual demand. Demand shaping strategies such as pricing can be used to shift elastic demand to reduce the imbalance. In this work, we propose to consider elastic demand in the forecasting phase. We present a method to reallocate the historical elastic…

2018-09-09abs ↗pdf ↗

The elastic flow, which is the L2L^2-gradient flow of the elastic energy, has several applications in geometry and elasticity theory. We present stable discretizations for the elastic flow in two-dimensional Riemannian manifolds that are conformally flat, i.e.\ conformally equivalent to the Euclidean space. Examples in…

2018-11-15abs ↗pdf ↗

Study shows global invertibility in nonlinear elasticity with vanishing self-repulsion term.

problem Global invertibility in nonlinear elasticity with a vanishing nonlocal self-repulsion term.
method Proves global invertibility in the ΓΓ-limit of elastic energy with a vanishing nonlocal self-repulsion term.
result Global invertibility can be obtained in the ΓΓ-limit of the elastic energy with a vanishing nonlocal self-repulsion term.

Study on surfaces minimizing elastic energy with boundary constraints.

problem Finding stable configurations of surfaces with elastic boundaries and surface energy.
method Investigation of critical surfaces with mean curvature and spontaneous curvature, coupled to boundary elastic energy.
result Characterization and minimization of surface energy for specific topological shapes.