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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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48 results for max-stable fields

Estimates derivatives of max-stable fields for risk analysis.

problem Estimating derivatives of max-stable random fields.
method Two unbiased stochastic derivative estimation approaches: Likelihood Ratio Method (LRM) and Infinitesimal Perturbation Analysis (IPA).
result Proposes conditions for the validity of LRM and IPA in Brown--Resnick and Smith fields.

An accurate assessment of the risk of extreme environmental events is of great importance for populations, authorities and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a corresponding set of axioms which are well suited to analyze the risk due to events having …

2018-03-19abs ↗pdf ↗

This paper develops DRO estimators for EVT statistics using point processes.

problem Scarcity of extreme data leads to model misspecification error in EVT.
method Developed DRO estimators informed by semi-parametric max-stable constraints in the space of point processes.
result Proposed DRO estimators improve out-of-sample performance and are validated on synthetic and real data.

Divide-and-conquer framework speeds up black-box inference for large data.

problem Computational intractability of uncertainty quantification for expensive data simulation.
method Divide data into partitions, train on a subset, bootstrap on partitions, combine results.
result Feasibility of estimating max-stable process parameters with tens of thousands of locations.

Proposes flexible spatial models for better understanding spatial heterogeneity.

problem Poor characterisation of spatial heterogeneity in conventional models.
method Spatial Bayesian Neural Networks (SBNNs) incorporating a spatial embedding layer and possibly spatially-varying parameters.
result SBNNs better match the finite-dimensional distribution of target spatial processes.

Efficient neural Bayes estimators for censored peaks-over-threshold models improve inference speed and accuracy.

problem Computational burden in inference with spatial extremal dependence models due to intractable or censored likelihoods.
method Developed neural Bayes estimators using data augmentation techniques to encode censoring information.
result Significant gains in computational and statistical efficiency compared to traditional methods.

Graph neural networks extend neural Bayes estimators to irregular spatial data.

problem Estimating parameters from irregular spatial data with computational efficiency.
method Employing graph neural networks to approximate Bayes estimators for irregular spatial data.
result Extending neural Bayes estimation to irregular spatial data with computational benefits.

Characterizes winding of braided vector fields in tubular domains.

problem Understanding the topology of braided vector fields in complex domains.
method Defines field line winding as a measure of entanglement, proving its uniqueness in classifying vector field topology.
result Field line winding uniquely classifies the topology of braided vector fields.

Every smooth vector field is a combination of gradient fields.

problem Expressing arbitrary smooth vector fields as combinations of gradient fields.
method Proving every smooth vector field can be written as a finite linear combination of iterated Lie brackets of gradient vector fields.
result Every smooth vector field is a combination of gradient fields.

The paper proves that certain modified conformal vector fields are trivial on compact and non-compact manifolds.

problem Proving triviality of modified conformal vector fields on Riemannian manifolds.
method Analyzing properties of homothetic, conformal, and gradient vector fields on compact and non-compact manifolds.
result Established conditions under which mm-modified conformal vector fields are trivial.

We prove a monodromy theorem for local vector fields belonging to a sheaf satisfying the unique continuation property. In particular, in the case of admissible regular sheaves of local fields defined on a simply connected manifold, we obtain a global extension result for every local field of the sheaf. This generalizes…

2015-07-13abs ↗pdf ↗

The paper establishes a connection between force-free fields and conformally geodesic fields.

problem Understanding the relationship between force-free fields and conformally geodesic fields.
method Developed an equivalence between force-free fields and conformally geodesic fields, generalized to arbitrary dimensions.
result Established that stationary points of hierarchies of L2L^2 and L1L^1-optimization problems are related by a conformal change of metric.

Study proves density of harmonic fields in continuous quaternion fields.

problem Characterizing harmonic quaternion fields and their density in continuous fields.
method Analyzes harmonic quaternion fields on smooth compact Riemannian manifolds, proving density via Stone-Weierstrass theorem.
result Subalgebra generated by harmonic fields is dense in continuous quaternion fields.

Vector fields invariant under Lie group action are finitely generated by polynomial fields.

problem Understanding invariant vector fields under Lie group actions.
method Analyzing the module of smooth vector fields invariant under a linear action of a compact Lie group.
result The module of invariant vector fields is finitely generated by polynomial fields.

The position vector field x is the most elementary and natural geometric object on a Euclidean submanifold MM. The position vector field plays very important roles in mathematics as well as in physics. Similarly, the tangential component x^T of the position vector field is the most natural vector field tangent to the …

2017-12-24abs ↗pdf ↗

This work discovers latent field effects governing interacting dynamical systems.

problem Discovering field effects governing interacting dynamical systems.
method Proposes neural fields to learn latent force fields from observed dynamics, disentangling local object interactions and global field effects.
result Accurately discovers latent field effects in various dynamical systems.

Study on vector fields on Lie groups reveals surprising algebraic coincidences.

problem Characterizing vector fields on Lie groups with Riemannian metrics.
method Algebraic and geometric analysis of left-invariant vector fields on nilpotent Lie groups.
result Spaces of Killing, one-harmonic, and conformal vector fields coincide with the center of the Lie algebra on nilpotent Lie groups.

Study proves conformal vector fields on certain Finsler manifolds are Killing fields.

problem Characterizing conformal vector fields on compact homogeneous Finsler manifolds.
method Analyzes properties of conformal vector fields and homogeneous Finsler metrics.
result Conformal vector fields on compact homogeneous Finsler manifolds are Killing fields.

For a submanifold M in a Euclidean space, the tangential component x^T of the position vector field x of M is the most natural vector field tangent to the Euclidean submanifold, called the canonical vector field of M. In this article, first we prove that the canonical vector field of every Euclidean submanifold is alwa…

2018-01-22abs ↗pdf ↗

Study magnetic field evolution in inhomogeneous axion stars.

problem Magnetic field evolution in axion stars with spatial inhomogeneity.
method Derived new induction equation for magnetic field, analyzed CS waves interactions, and considered compact domain effects.
result Spatial inhomogeneity of pseudoscalar field significantly affects magnetic field evolution.

Challenge to separate Earth's magnetic field from vehicle's magnetic field for accurate navigation.

problem Separate Earth's magnetic field from vehicle's magnetic field for accurate magnetic navigation.
method Use machine learning (ML) and integrate physics of magnetic navigation (SciML) to remove aircraft magnetic field from total magnetic field.
result A model can be constructed to effectively remove aircraft magnetic field from the dataset.

A Ricci soliton (M,g,v,λ)(M,g,v,λ) on a Riemannian manifold (M,g)(M,g) is said to have concurrent potential field if its potential field vv is a concurrent vector field. Ricci solitons arisen from concurrent vector fields on Riemannian manifolds were studied recently in \cite{CD2}. The most important concurrent vector field is …

2014-10-19abs ↗pdf ↗

New field invariant refines real spectrum and relates to absolute Galois group.

problem Understanding field invariants related to absolute Galois groups.
method Introducing Artin-Schreier quandles and computing their properties for different types of fields.
result Artin-Schreier quandles provide relations between fields and their absolute Galois groups.

Study biharmonic vector fields and unit vector fields on Riemannian manifolds.

problem Determine the equivalence of biharmonicity and harmonicity for vector fields and unit vector fields on Riemannian manifolds.
method Analyze biharmonic vector fields and unit vector fields on (M,g)(M,g) with pseudo-Riemannian gg-natural metrics on TMTM and T1MT_1M.
result Contrary to Sasaki metric, biharmonicity and harmonicity are not equivalent for large classes of gg-natural metrics on TMTM.

Semisimple 4D field theories can't distinguish smooth 4-manifolds.

problem Detecting exotic smooth structures in 4-manifolds.
method Proving field theories lead to stable invariants, distinguishing only homeomorphic and homotopy equivalent manifolds.
result Semisimple 4D field theories can't distinguish homotopy equivalent 4-manifolds.

This short report establishes some basic properties of smooth vector fields on product manifolds. The main results are: (i) On a product manifold there always exists a direct sum decomposition into horizontal and vertical vector fields. (ii) Horizontal and vertical vector fields are naturally isomorphic to smooth famil…

2011-06-05abs ↗pdf ↗

Defines quaternionic k-vector fields on quaternionic Kähler manifolds.

problem No specific problem stated; focuses on definition and properties.
method Introduced a modified Dirac operator to define quaternionic k-vector fields.
result Calculated the dimension of quaternionic k-vector fields on HPn\mathbb{H}P^n.

The paper classifies Killing tensor fields on Riemannian symmetric spaces.

problem Understanding Killing tensor fields on Riemannian symmetric spaces.
method Reduced study to compact irreducible spaces, introduced top slot Killing tensor fields, and classified quadratic fields.
result Quadratic Killing tensor fields on Riemannian symmetric spaces of rank one are spanned by top-slot and decomposable fields.

A spiking neural network model for probabilistic inference of binary Markov random fields.

problem Implementing probabilistic inference in spiking neural networks.
method Designing a spiking recurrent neural network and proving its equivalence to mean-field inference of binary Markov random fields.
result The spiking neural network model can implement inference of arbitrary binary Markov random fields.

A vector field on a Riemannian manifold is called conformal Killing if it generates one-parameter group of conformal transformations. The class of conformal Killing symmetric tensor fields of an arbitrary rank is a natural generalization of the class of conformal Killing vector fields, and appears in different geometri…

2011-03-18abs ↗pdf ↗