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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.

168,695 papers · 148 categories

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2925848751,167 · Jun 202019922001200920172026
48 results for boundary data

Study finds rigid properties of boundary-free hypersurfaces in specific data sets.

problem Rigidity of free boundary hypersurfaces in initial data sets with boundary.
method Extending local splitting theorems and applying results on free boundary MOTS.
result Rigidity results for compact free boundary hypersurfaces in initial data sets with boundary.

We establish a moduli space E\mathbb E of stationary vacuum metrics in a spacetime, and set up a well-defined boundary map ΠΠ in E\mathbb E, assigning a metric class with its Bartnik boundary data. Furthermore, we prove the boundary map ΠΠ is Fredholm by showing that the stationary vacuum equations (combined with p…

2018-07-01abs ↗pdf ↗

Paper proves rigidity of initial data sets with boundary and capillary MOTS.

problem Rigidity of initial data sets with boundary and capillary MOTS.
method Estimates area of MOTS, proves rigidity for 3D, extends to high dimensions using Yamabe constant.
result Rigidity results for initial data sets with boundary and capillary MOTS.

Proves well-posedness for Einstein equations with specific boundary data.

problem Proving well-posedness for Einstein equations with Dirichlet boundary data.
method Local-in-time well-posedness proof for vacuum Einstein equations with specific boundary conditions.
result Proves well-posedness for Einstein equations with Dirichlet boundary data under convexity-type assumptions.

Geometric data uniquely determines convex subsets in hyperbolic manifolds.

problem Determining convex subsets in hyperbolic manifolds based on boundary data.
method Using conformal structure, induced metric, and third fundamental form on boundary components.
result Convex subsets are uniquely determined by boundary data.

For a compact Riemannian manifold with boundary, we want to find the metric structure from knowledge of distances between boundary points. This is called the "boundary rigidity problem". If the boundary is not concave, which means locally not all shortest paths lie entirely in the boundary, then we are able to find the…

2011-03-28abs ↗pdf ↗

Proves well-posedness for Einstein equations with specific boundary conditions.

problem Well-posedness of vacuum Einstein equations with twisted Dirichlet boundary conditions.
method Proves local-in-time well-posedness for the IBVP of the Einstein equations with specified conformal class and scalar densities.
result Proves well-posedness for the Einstein equations with twisted Dirichlet boundary conditions.

One-Class Boundary Peeling detects outliers efficiently and robustly.

problem Unsupervised outlier detection in diverse data distributions.
method One-Class Boundary Peeling uses flexible boundaries generated by one-class SVMs and iteratively peels them.
result One-Class Boundary Peeling outperforms state-of-the-art methods in synthetic data simulations.

Area-charge inequalities and local rigidity of free boundary MOTS in charged initial data sets

problem Area-charge inequalities and local rigidity of free boundary MOTS in charged initial data sets
method Area-charge inequalities and local rigidity of free boundary MOTS in charged initial data sets
result Prove area-charge inequalities for free boundary MOTS in initial data sets for the Einstein-Maxwell equations with vanishing magnetic fields

The paper recovers contact forms from boundary data using vector fields and Lyapunov functions.

problem Recovering contact forms from boundary data.
method Using vector fields and Lyapunov functions, the paper describes boundary data and proves reconstruction of (X,β)(X, β) up to diffeomorphism.
result Boundary data allow for the reconstruction of (X,β)(X, β) up to a diffeomorphism of XX.

We study the short-time existence and regularity of solutions to a boundary value problem for the Ricci-DeTurck equation on a manifold with boundary. Using this, we prove the short-time existence and uniqueness of the Ricci flow prescribing the mean curvature and conformal class of the boundary, with arbitrary initial …

2012-10-02abs ↗pdf ↗

New static vacuum metrics confirmed for near Euclidean boundary data.

problem Establishing sufficient conditions for near Euclidean boundary data in static vacuum metrics.
method Using new arguments from studying the conjecture for arbitrary static vacuum metrics.
result Any hypersurface in a dense subfamily is static regular.

Analyzes Willmore flow for graphs with boundary data, proving existence and convergence.

problem Willmore flow of graphs with boundary conditions over bounded domains.
method Developed low-regularity theory, reformulated graphical equation, used time-weighted parabolic Hölder spaces.
result Proved short-time and global existence for initial data in C1+α(Ω)C^{1+α}(\overlineΩ) and Lipschitz, with exponential convergence.

This paper improves boundary regularity of harmonic maps in metric measure spaces.

problem Improving boundary regularity of harmonic maps in non-smooth spaces.
method Developed a Gauss-Green formula for RCD(K,N)RCD(K, N) spaces and applied it to harmonic maps.
result Optimal boundary regularity of harmonic maps from RCD(K,N)RCD(K,N)-spaces to CAT(0)CAT(0)-spaces.

Study on well-posedness of vacuum Einstein equations with specific boundary conditions.

problem Well-posedness of the initial boundary value problem for vacuum Einstein equations with geometric boundary conditions.
method Analysis of conformal-mean curvature boundary data, proving dense solution space and Holmgren-type uniqueness theorem.
result Linearized problem has a solution space with dense range in CC^{\infty}, valid for general smooth linearized solutions.

Proposes a boundary detection method inspired by LLE for high-dimensional data.

problem Identifying boundary points from data on an embedded manifold.
method Inspired by locally linear embedding, uses nearest neighbor search schemes and spectral properties of local covariance matrix.
result Enhanced boundary detection in noisy data.

Explains how to prove positive mass theorem with boundary in dimensions less than 8.

problem Proving the positive mass theorem with boundary conditions.
method Uses established results to prove various versions of the theorem.
result Various versions of the positive mass theorem are proven for initial data sets with boundary in dimensions less than 8.

Proves rigidity for specific initial data sets under the dominant energy condition.

problem Rigidity of initial data sets with boundary and convex polytopes.
method Solution of boundary value problems for Dirac operators and approximations by manifolds with smooth boundary.
result Proves rigidity for compact smooth spin manifolds and convex polytopes under the dominant energy condition.

The paper improves boundary detection and density estimation on noisy data.

problem Detecting boundary points and estimating density on noisy data from compact manifolds.
method Doubly stochastic scaling of the Gaussian heat kernel via Sinkhorn iterations.
result The new estimates of boundary points and density outperform standard methods, especially under noise.

We consider the classification problem and focus on nonlinear methods for classification on manifolds. For multivariate datasets lying on an embedded nonlinear Riemannian manifold within the higher-dimensional ambient space, we aim to acquire a classification boundary for the classes with labels, using the intrinsic me…

2017-10-21abs ↗pdf ↗

New method measures generalizability of deep neural networks based on decision boundary complexity.

problem Lack of generalization methods for deep neural networks.
method Created Decision Boundary Complexity (DBC) score to measure DNN complexity.
result Simpler decision boundaries lead to better generalizability, supporting Occam's Razor.

This article is based on a lecture at the Journal of Differential Geometry Conference, Harvard 2017. We discuss closed and torsion-free G2G_{2}-structures on a 7-manifold with boundary, with prescribed 33-form on the boundary. Much of the article is based on an observation that there is an intrinsic notion of "mean co…

2018-02-27abs ↗pdf ↗

Extends static vacuum metrics with specific boundary conditions.

problem Proving the existence of static vacuum metrics with prescribed boundary data.
method Introducing static regular types (I) and (II), showing local well-posedness, and confirming Bartnik's conjecture.
result Confirms Bartnik's static vacuum extension conjecture for a broad range of boundary conditions.

In this paper we consider the lens rigidity problem with partial data for conformal metrics in the presence of a magnetic field on a compact manifold of dimension 3\geq 3 with boundary. We show that one can uniquely determine the conformal factor and the magnetic field near a strictly convex (with respect to the magne…

2016-05-20abs ↗pdf ↗

We prove identification of coefficients up to gauge by Cauchy data at the boundary for elliptic systems on oriented compact surfaces with boundary or domains of C\mathbb{C}. In the geometric setting, we fix a Riemann surface with boundary, and consider both a Dirac-type operator plus potential acting on sections of a …

2011-05-23abs ↗pdf ↗

Proves spacetime positive mass theorem for spin initial data sets with arbitrary ends.

problem Proving the spacetime positive mass theorem for specific spacetime configurations.
method Solving a mixed boundary value problem for the Dirac-Witten operator with a Callias potential.
result Established spacetime positive mass theorem for asymptotically flat spin initial data sets with arbitrary ends.

The paper shows how neural networks with less decision boundary variability generalize better.

problem Improving neural network generalizability by reducing decision boundary variability.
method Introduces new measures (algorithm DB variability and (ε,η)(ε, η)-data DB variability) to quantify decision boundary variability and proves theoretical bounds on generalizability.
result Neural networks with lower decision boundary variability have better generalizability, as shown by extensive experiments and theoretical bounds.

The paper introduces boundary thickness as a measure for improving model robustness.

problem Improving the robustness of machine learning models to adversarial and non-adversarial corruptions.
method Introducing boundary thickness as a measure and showing how various procedures can increase it.
result Thicker decision boundaries lead to improved robustness against adversarial and out-of-distribution transforms.

Let (M,g) be a compact Einstein manifold with smooth boundary. We consider the spectrum of the p form valued Laplacian with respect to a suitable boundary condition. We show that certain geometric properties of the boundary may be spectrally characterized in terms of this data where we fix the Einstein constant.

2003-05-07abs ↗pdf ↗

Willmore flow converges globally for surfaces with rotational symmetry below a specific energy threshold.

problem Global existence and convergence of Willmore flow with Dirichlet boundary conditions.
method Considered surfaces with rotational symmetry, proved global existence and convergence for initial data below a sharp energy threshold.
result Sharp threshold for global existence and convergence of Willmore flow depends on boundary conditions.

We investigate the validity of the isometry extension property for (Riemannian) Einstein metrics on manifolds with boundary. Given a metric on the boundary, this is the issue of whether any Killing field of the boundary metric extends to a Killing field of any bulk or filling Einstein metric inducing the given data on …

2007-04-25abs ↗pdf ↗

Developing deformation theory for Calabi-Yau 3-folds with boundary.

problem Dealing with Calabi-Yau threefolds on manifolds with boundary.
method Deformation theory and local Torelli Theorem for compact manifolds.
result An analogue of Hitchin's local Torelli Theorem for Calabi-Yau 3-folds with boundary, modulo a finite dimensional obstruction space.