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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.

169,341 papers · 148 categories

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70140209279 · Jun 202019922001200920182026
48 results for Lipschitz-Killing measures

Abstract relates Lipschitz-Killing measures to polar volumes of definable sets.

problem Relating geometric measures of definable sets to their polar images.
method Relates Lipschitz-Killing measures to volumes of generic polar images for smooth submanifolds, extending to infinitesimal versions.
result Establishes a relation between polar invariants and densities of generic polar images.

Paper classifies curvature measures and confirms a conjecture.

problem Classifying curvature measures and proving the angularity conjecture.
method Investigation of translation-invariant angular curvature measures and use of isometric immersions and Lipschitz-Killing algebra.
result Confirmation of the angularity conjecture.

Fractal Lipschitz-Killing curvature measures C^f_k(F,.), k = 0, ..., d, are determined for a large class of self-similar sets F in R^d. They arise as weak limits of the appropriately rescaled classical Lipschitz-Killing curvature measures C_k(F_r,.) from geometric measure theory of parallel sets F_r for small distances…

2010-07-05abs ↗pdf ↗

Applying a local Gauss-Bonnet formula for closed subanalytic sets to the complex analytic case, we obtain characterizations of the Euler obstruction of a complex analytic germ in terms of the Lipschitz-Killing curvatures and the Chern forms of its regular part. We also prove analogous results for the global Euler obstr…

2014-05-23abs ↗pdf ↗

Study of cosmic microwave background polarization using spin random fields.

problem Detecting deviations from Gaussianity and anisotropies in cosmic fields.
method Explicit formula for Lipschitz-Killing curvatures of spin spherical random fields.
result Coherent with asymptotic results, providing new metric expressions.

We show how Alesker's theory of valuations on manifolds gives rise to an algebraic picture of the integral geometry of any Riemannian isotropic space. We then apply this method to give a thorough account of the integral geometry of the complex space forms, i.e. complex projective space, complex hyperbolic space and com…

2012-04-03abs ↗pdf ↗

Developed new Crofton formulas for pseudo-Riemannian spaces.

problem Computing volumes and curvature integrals in pseudo-Riemannian space forms.
method Introduced Crofton formulas using distributions and Alesker's Radon transform.
result Explicit Crofton formulas for all isometry-invariant valuations on pseudo-Riemannian spaces.

Study on spin random fields using chaos decomposition for cosmic microwave background modeling.

problem Modeling polarization of Cosmic Microwave Background using spin random fields.
method Explicit Wiener-Itô chaos decomposition of area measures of level sets.
result Reveals a clear difference between high frequency regime and zero spin case.

The paper characterizes the geometry and topology of spin random fields.

problem Understanding the expected geometry and topology of spin random fields.
method Investigating the asymptotic behavior of geometric and topological functionals for spin random fields under scaling assumptions.
result Explicit results for monochromatic fields, showing non-universal asymptotic behavior and new generalized models.

Thurston's circle packing approximation of the Riemann Mapping (proven to give the Riemann Mapping in the limit by Rodin-Sullivan) is largely based on the theorem that any topological disk with a circle packing metric can be deformed into a circle packing metric in the disk with boundary circles internally tangent to t…

2014-07-25abs ↗pdf ↗

For germs of subanalytic sets, we define two finite sequences of new numerical invariants. The first one is obtained by localizing the classical Lipschitz-Killing curvatures, the second one is the real analogue of the evanescent characteristics introduced by M. Kashiwara. We show that each invariant of one sequence is …

2007-06-27abs ↗pdf ↗

GeoTop resolves topological ambiguity in diagnostic imaging using geometric-topological analysis.

problem Topological equivalence between benign and malignant structures in diagnostic images.
method Combines Topological Data Analysis and Lipschitz-Killing Curvatures to resolve ambiguity.
result Achieves 3.6% accuracy improvement and reduces false positives/negatives by 15-18%.

We study the differential geometric consequences of our previous result on the existence of fat triangulations, in conjunction with a result of Cheeger, Müller and Schrader, regarding the convergence of Lipschitz-Killing curvatures of piecewise-flat approximations of smooth Riemannian manifolds. A further application t…

2011-08-17abs ↗pdf ↗

We consider vector valued, unit variance Gaussian processes defined over stratified manifolds and the geometry of their excursion sets. In particular, we develop an explicit formula for the expectation of all the Lipschitz--Killing curvatures of these sets. Whereas our motivation is primarily probabilistic, with statis…

2006-12-20abs ↗pdf ↗

Weyl's intrinsic volumes converge to the Euler characteristic of the base manifold under certain metrics.

problem Convergence of intrinsic volumes on Riemannian manifolds.
method Defined a new metric and used it to study the convergence of intrinsic volumes.
result Intrinsic volumes converge to the Euler characteristic of the base manifold.

The paper studies residues of manifolds and their applications in geometry.

problem Understanding the residues of manifolds and their geometric implications.
method Analytic continuation and Möbius invariance of residues, introduction of relative and weighted residues.
result Scalar curvature, mean curvature, and Euler characteristic can be expressed in terms of residues.

Study invariant measures on measured laminations for subgroups of mapping class group.

problem Classify invariant Radon measures on space of measured laminations for subgroups of mapping class group.
method Geometric approach, focusing on recurrent measured laminations, explicitly constructing ergodic measures.
result Show uniquely ergodic for divergence-type subgroups, generalize results for full mapping class group.

New set-valued star-shaped risk measures introduced for better risk assessment.

problem Improving risk assessment in financial contexts.
method Developed new set-valued star-shaped risk measures and proved their representation theorems.
result Set-valued star-shaped risk measures can be represented as unions of set-valued convex risk measures.

Bayesian approach to robust risk measures under model uncertainty.

problem Representing robust risk measures as a single probability measure.
method Introducing two types of risk measures and analyzing their relation to robust risk measures.
result Robust risk measures can be represented by a mixture probability measure, a Bayesian approach.

Survey of time consistency in dynamic risk and performance measures using LM-measure.

problem Time consistency of dynamic risk and performance measures in discrete time.
method Focus on LM-measure and update rule to study time consistency.
result Comprehensive overview of time consistency properties.

The paper classifies 1-dimensional uniform measures in various dimensions.

problem Classifying uniformly distributed measures of dimension 1 in general codimension.
method Analyzing measures with connected 1-dimensional support and providing a partial classification for general measures.
result Uniform measures with connected 1-dimensional support are homogeneous measures.

The paper studies dynamic star-shaped risk measures and their representation.

problem Representing dynamic star-shaped risk measures and their properties.
method Representation theorems for dynamic monetary and star-shaped risk measures.
result Dynamic star-shaped risk measures can be represented as the lower envelope of a family of dynamic convex risk measures.

Transformers can interpolate between arbitrary measures.

problem Understanding the expressive power of Transformers as measure-to-measure maps.
method Provided an explicit choice of parameters for a single Transformer to match N arbitrary input measures to N arbitrary target measures.
result A single Transformer can interpolate between arbitrary measures.

Researchers compute the ratio between two normalizations of Thurston measure on measured laminations.

problem Computing the ratio between two normalizations of Thurston measure.
method Using the integral and symplectic structures on the space of measured laminations.
result Computed the ratio between two normalizations of Thurston measure.

A new method calculates a barycenter for probability measures using Wasserstein distance.

problem Finding a central measure for a set of probability distributions.
method Regularizing the pushforward measure of a set of probability distributions into the Wasserstein space and then finding the barycenter.
result The method yields a uniquely defined barycenter measure supported on the barycentric points of the input measures.

New Bayesian method for spectral deconvolution with Poisson noise.

problem Estimating physical model parameters from noisy spectral data.
method Bayesian measurement framework applied to Poisson noise model.
result Clarifies relationship between measurement time and estimation limits.

Submodularity is studied for convex risk measures, including Expected Shortfall.

problem Characterizing submodularity in convex risk measures.
method Analyzing submodularity properties of law-invariant coherent risk measures, including Expected Shortfall and Value-at-Risk.
result AES is submodular only when it reduces to ES, and empirical analysis shows AES violations are less frequent than VaR and ES violations.

Paper compares graph and set partition measures for graph clustering.

problem Comparing graph clustering methods using different similarity measures.
method Introduces graph-aware partition similarity measures and compares them with set partition measures.
result Graph-aware measures provide complementary information to set partition measures.

The paper explores non-convex risk measures and their characterizations.

problem Characterizing non-convex risk measures without convexity or weak convexity.
method Characterizes monetary risk measures as lower envelopes of families of convex or coherent risk measures, considering law-invariance and SSD-consistency.
result Unified representation theorems for law-invariant risk measures, including VaR.