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arXiv research

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.

169,051 papers · 148 categories

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285683111 · May 202619922001200920182026
48 results for elastic alignment

A new FFT-based method for fast rigid alignment of 2D closed curves.

problem Rigid alignment of 2D closed curves with application to shape analysis.
method FFT-based algorithm for optimal rigid alignment of closed curves with O(N log N) complexity.
result Order of magnitude speed-up in curve alignment compared to previous methods.

New method shortens and straightens curves, proving convergence and well-posedness.

problem Shortening and straightening of curves.
method Conceptual shift in curve shortening to tangent aligning, variational study of geometric flows.
result Proves convergence to a straight line and global well-posedness for various geometric flows.

DET unifies geometric and functional alignment for high-dimensional scientific data.

problem Challenges in nonrigid registration for high-dimensional, irregular data.
method Domain Elastic Transform (DET) treats data as functions on irregular domains, using a Bayesian framework for elastic motion registration.
result DET achieves 92% topological preservation on MERFISH data and successfully registers whole-embryo Stereo-seq atlases.

EAGC boosts GCD by regulating gradient entanglement, improving known and novel category separability.

problem Gradient entanglement distorts supervised gradients and overlaps known and novel class representations.
method EAGC uses AGA and EEP to align and project gradients, reducing entanglement and overlap.
result EAGC consistently boosts GCD performance, setting new state-of-the-art results.

DeepFRC learns both alignment and classification of functional data in one model.

problem Phase variability in functional data obscures underlying patterns and degrades model performance.
method End-to-end deep learning framework that combines diffeomorphic warping functions and a classifier.
result DeepFRC outperforms state-of-the-art methods in both alignment quality and classification accuracy.

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.

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.

Local elasticity in neural networks makes predictions resilient to dissimilar updates.

problem Understanding resilience of neural network predictions to updates from dissimilar data.
method Simulation and geometric interpretation using neural tangent kernel.
result Local elasticity persists in neural networks with nonlinear activation functions, not in linear ones.

Study elastic Dirichlet-to-Neumann map to uniquely determine metrics and spectral invariants.

problem Uniquely determine metrics of Riemannian manifolds from elastic Dirichlet-to-Neumann maps.
method Explicitly get matrix-valued full symbol for elastic Dirichlet-to-Neumann map, prove metric uniqueness, calculate spectral invariants.
result Elastic Dirichlet-to-Neumann map uniquely determines the metric of a real-analytic Riemannian manifold.

Enhanced Elastic-Net with box-constraint improves support recovery in noisy measurements.

problem Support recovery of sparse signals from noisy measurements.
method Box-Elastic Net (Box-EN) method with mean squared error and probability of support recovery analysis.
result The Box-Elastic Net outperforms the standard Elastic-Net in support recovery.

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 ↗

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.

Elastic Gossip distributes neural network training using gossip-like protocols.

problem Distributing neural network training across heterogeneous environments.
method Pairwise-communication using Gossip-like protocols, building on Elastic Averaging SGD.
result Elastic Gossip performs better than Gossiping SGD in experiments, but hyper-parameter search may yield better configurations.

Chicle tackles elastic machine learning training by avoiding micro-tasks.

problem Elasticity and load balancing in distributed machine learning training.
method Chicle is a new elastic distributed training framework that exploits machine learning algorithms to implement elasticity and load balancing without micro-tasks.
result Chicle achieves performance competitive with state-of-the-art rigid frameworks while enabling elastic execution and dynamic load balancing.

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.

Study on elasticity with mixed boundary conditions, proving spectral asymptotics.

problem Analyzing spectral asymptotics for linear elasticity with mixed boundary conditions.
method Established two-term spectral asymptotics for linear elasticity on smooth compact manifolds.
result Verification of general formulae through explicit examples in 2D and 3D.

Straight lines are a basin of attraction for the elastic flow at least to level 1.9615π.

problem Understanding the basin of attraction for the free boundary free elastic flow.
method Steepest descent gradient flow for elastic energy, numerical evidence.
result Straight lines have a basin of attraction at least to level 1.9615π.

Study a flow for curve energy, proving existence for various p.

problem Evolution of closed curves under energy minimization.
method Second order flow decreasing p-elastic energy, proving existence via minimizing movements.
result Existence of solutions for p(1,)p \in (1, \infty), long-time existence for p=2p = 2.

Study on hyperbolic elastic flow, proving convergence and quantifying singularities.

problem Understanding singularities and convergence of elastic flow in hyperbolic plane.
method Analyzes closed and open curves with clamped boundary conditions, proving convergence without small energy assumption.
result Each singularity carries an energy cost of at least 8, and blow-ups are explicitly classified.