Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

122244365487 · Jun 202019922001200920172026
48 results for metric dependence

Paper shows how scattering maps of Schrödinger equations relate to metrics.

problem Relating scattering maps of time-dependent Schrödinger equations to metrics.
method Analyzes scattering maps for specific classes of metrics and diffeomorphisms.
result Scattering maps differ by a compact operator if and only if metrics are related by diffeomorphism.

Few-shot learning has become essential for producing models that generalize from few examples. In this work, we identify that metric scaling and metric task conditioning are important to improve the performance of few-shot algorithms. Our analysis reveals that simple metric scaling completely changes the nature of few-…

2018-05-23abs ↗pdf ↗

Artificial neural networks (NN) are instrumental in realizing highly-automated driving functionality. An overarching challenge is to identify best safety engineering practices for NN and other learning-enabled components. In particular, there is an urgent need for an adequate set of metrics for measuring all-important …

2018-06-06abs ↗pdf ↗

Metric learning enhances combinatorial coverage metrics' ability to predict classification errors.

problem Dataset dependence of combinatorial coverage metrics in anticipating classification errors.
method Metric learning to improve latent space separation of data classes.
result Metric learning increases SDCCMs' ability to distinguish between correctly and incorrectly classified data.

Learning a good distance measure for distance-based classification in time series leads to significant performance improvement in many tasks. Specifically, it is critical to effectively deal with variations and temporal dependencies in time series. However, existing metric learning approaches focus on tackling variatio…

2019-10-23abs ↗pdf ↗

MDS selects assets by combining daily returns and intraday risk curves, improving portfolio performance.

problem High estimation error in large-scale asset selection.
method Metric Dependence Screening (MDS) incorporating high frequency information as object valued data.
result MDS improves portfolio performance over benchmarks by preserving intraday risk dynamics.

Develops new synthetic Ricci flow concepts for metric measure spaces.

problem No specific problem stated; focuses on new mathematical concepts.
method Formulated in terms of dynamic convexity and local concavity of entropy, and global/short-time asymptotic transport cost estimates.
result Shows these properties characterise smooth (weighted) Ricci flows.

Stability of cut locus under metric perturbations in compact Riemannian manifolds.

problem Stability of cut locus under C2C^2-perturbations of the metric.
method Proving stability with respect to the Hausdorff metric of the cut locus under C2C^2 perturbation of the metric.
result The Hausdorff distance between cut loci converges to zero as the metrics converge.

Paper investigates conditions for independence of weak gradients on metric spaces.

problem Dependence of weak gradients on pp in arbitrary metric measure spaces.
method Investigates the Bounded Interpolation Property to ensure independence of weak gradients.
result Bounded Interpolation Property guarantees independence of weak gradients.

Study reveals class-dependent effects in perturbation-based feature attribution metrics for time series classification.

problem Varying effectiveness of perturbation-based metrics across different classes in time series models.
method Systematic empirical analysis across multiple datasets, model architectures, and perturbation strategies.
result Perturbation-based metrics show varying effectiveness across classes, with some metrics performing better for certain classes.

Our results concern geometry of a manifold endowed with a pair of complementary orthogonal distributions (plane fields) and a time-dependent Riemannian metric. The work begins with formulae concerning deformations of geometric quantities as the Riemannian metric varies conformally along one of the distributions. Then w…

2011-09-09abs ↗pdf ↗

Derives derivatives and geometric framework for functions with non-independent variables.

problem Characterizing functions with non-independent variables in probabilistic models.
method Derives actual and dependent partial derivatives, dependent Jacobian matrix, and tensor metric.
result Derives gradient, Hessian, and Taylor expansion for functions with non-independent variables.

We prove that the TTTT-gauge-fixed linearised Einstein operator is non-degenerate for Riemannian Kottler ("Schwarzschild-anti de Sitter") metrics with dimension- and topology-dependent ranges of mass parameter. We provide evidence that this remains true for all such metrics except the spherical ones with a critical mas…

2017-10-20abs ↗pdf ↗

We study the geometry of a codimension-one foliation with a time-dependent Riemannian metric. The work begins with formulae concerning deformations of geometric quantities as the Riemannian metric varies along the leaves of the foliation. Then the Extrinsic Geometric Flow depending on the second fundamental form of the…

2011-08-25abs ↗pdf ↗

We prove that the "generic condition" used in singularity theorems of general relativity is generic in the space of Lorentzian metrics on a given manifold, in the sense that it is satisfied for all metrics in a residual set in the Whitney CkC^k-topology, for kk depending on the dimension of the manifold.

2017-01-25abs ↗pdf ↗

Tian initiated the study of incomplete Kähler-Einstein metrics on quasi-projective varieties with cone-edge type singularities along a divisor, described by the cone-angle 2π(1α)2π(1-α) for α(0,1)α\in (0, 1). In this paper we study how the existence of such Kähler-Einstein metrics depends on αα. We show that in the negative s…

2012-09-30abs ↗pdf ↗

Proposes an online metric learning method for multi-label classification.

problem Lack of consideration for label dependencies and theoretical analysis of loss functions in existing multi-label classification methods.
method Develops a novel online metric learning paradigm based on k-Nearest Neighbour (kNN) and large margin principle, adapted for online streaming data.
result The proposed OML algorithm outperforms state-of-the-art methods on benchmark multi-label datasets.

We present a systematic study of causality theory on Lorentzian manifolds with continuous metrics. Examples are given which show that some standard facts in smooth Lorentzian geometry, such as light-cones being hypersurfaces, are wrong when metrics which are merely continuous are considered. We show that existence of t…

2011-11-02abs ↗pdf ↗

We define systems of pre-extremals for the energy functional of regular rheonomic Lagrange manifolds and show how they induce well-defined Hamilton orthogonal nets. Such nets have applications in the modelling of e.g. wildfire spread under time- and space-dependent conditions. The time function inherited from such a Ha…

2017-08-24abs ↗pdf ↗

The real Jacobi group G1J(R)G^J_1(\mathbb{R}), defined as the semi-direct product of the group SL(2,R){\rm SL}(2,\mathbb{R}) with the Heisenberg group H1H_1, is embedded in a 4×44\times 4 matrix realisation of the group Sp(2,R){\rm Sp}(2,\mathbb{R}). The left-invariant one-forms on G1J(R)G^J_1(\mathbb{R}) and their dual orthogonal left-i…

2019-03-26abs ↗pdf ↗

UK universities pension scheme valuation study shows high dependence on gilt yields.

problem High dependence of UK universities pension scheme on UK government bond yields.
method Analysis of USS valuations from 2014 to 2023, examination of self-sufficiency conditions, and evaluation of metrics.
result Second self-sufficiency condition amplifies gilt yield dependence, leading to inflated liabilities and excessive prudence.

Method finds approximate Ricci-flat metrics on Calabi-Yau manifolds.

problem Finding analytic Kähler potentials for Calabi-Yau manifolds.
method Numerically calculating Ricci-flat Kähler potentials via machine learning and fitting to Donaldson's Ansatz.
result Simple analytic expressions for approximately Ricci-flat Kähler potentials are found, including explicit dependence on complex structure parameter.

Deformations of Dubrovin's Hurwitz Frobenius manifolds are constructed. The deformations depend on g(g+1)/2g(g+1)/2 complex parameters where gg is the genus of the corresponding Riemann surface. In genus one, the flat metric of the deformed Frobenius manifold coincides with a metric associated with a one-parameter family of…

2004-08-15abs ↗pdf ↗

The paper proposes and proves asymptotic expansions for quantum invariants.

problem Quantum invariants and their expansions under varying metrics.
method Asymptotic expansion conjectures for relative Reshetikhin-Turaev, Turaev-Viro invariants and quantum 6j-symbols.
result Proved asymptotic expansions for special cases, showing geometric dependence on metrics.

An extension of the ambient metric construction of Fefferman-Graham to infinite order in even dimensions is described. The main ingredients are the introduction of "inhomogeneous ambient metrics" with asymptotic expansions involving the logarithm of a defining function homogeneous of degree 2, and an invariant procedur…

2006-11-30abs ↗pdf ↗

Wave propagation framework using cone structures and observers' vector fields.

problem Describing classic wave propagation in anisotropic media.
method Introduces a cone structure CC and an observers' vector field t\partial_t to describe wave propagation.
result Reduces the PDE for wavefronts to ODE for cone geodesics of CC.

Geodesic orbit metrics on real flag manifolds identified.

problem Classifying real flag manifolds with geodesic orbit metrics.
method Investigated invariant metrics on real flag manifolds, focusing on those where geodesics are orbits of one-parameter subgroups.
result Non-trivial geodesic orbit metrics exist on real flag manifolds, unlike in the complex case.

We prove the existence of an abundance of new Einstein metrics on odd dimensional spheres including exotic spheres, many of them depending on continuous parameters. The number of families as well as the number of parameter grows double exponentially with the dimension. Our method of proof uses Brieskorn-Pham singularit…

2003-09-24abs ↗pdf ↗

We provide a general framework to study convergence properties of families of maps. For manifolds MM and NN where MM is equipped with a volume form V\mathcal{V} we consider families of maps in the collection {(φ,B):BM,φ:BN with both measurable}\{(φ, B) : B \subset M, φ:B \rightarrow N\text{ with both measurable}\} and we define a distance function …

2014-06-16abs ↗pdf ↗

The paper analyzes convergence of Langevin dynamics with time-dependent metrics.

problem Analyzing convergence of Langevin dynamics with time-dependent metrics.
method Formulated a modified gradient flow of the Kullback-Leibler divergence, selected a time-dependent relative Fisher information functional, and developed a time-dependent Hessian matrix condition.
result Proved convergence conditions for various Langevin dynamics.