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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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23456890 · Jun 202019922001200920172026
48 results for inhomogeneous speeds

Study reconstructs Riemannian metric from Cherenkov radiation in complex media.

problem Reconstructing internal geometry of inhomogeneous anisotropic targets.
method Mathematical model of waves in medium, including vector-valued wave operator and phase velocity.
result Riemannian metric inside a bounded region can be reconstructed from boundary measurements of Cherenkov radiation.

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.

Study shows deformations of quaternionic Kähler manifolds are locally inhomogeneous.

problem Understanding deformations of quaternionic Kähler manifolds.
method Proved one-loop deformation of quaternionic Kähler manifolds are locally inhomogeneous.
result Full isometry group of one-loop deformations has cohomogeneity one.

We introduce a new parameter to measure the inhomogeneity of training datasets.

problem The need for non-stationary models in supervised learning.
method We introduce a new parameter, the inhomogeneity parameter, to measure the inhomogeneity of training datasets.
result A training set with a non-zero inhomogeneity parameter requires a non-stationary model for accurate predictions.

The paper studies inhomogeneous isoparametric hypersurfaces in pseudo-spheres.

problem Investigating inhomogeneous isoparametric hypersurfaces in pseudo-sphere.
method Construction of Clifford systems and analysis of isoparametric hypersurfaces.
result Connected isoparametric hypersurfaces of OT-FKM-type in pseudo-spheres are inhomogeneous under specific conditions.

Paper examines floating exercise boundaries for American options in time-inhomogeneous models.

problem Floating exercise boundaries in time-inhomogeneous models with negative interest rates or yields.
method Semi-analytical approach for pricing American options.
result Specialized pricing methodologies are required for models with floating exercise boundaries.

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics. A widely used method for hypergraph partitioning relies on minimizing a normalized sum of the costs of partitioning hyperedges across clusters. Algorithmic solutions based on this approach assume that different p…

2017-09-05abs ↗pdf ↗

Efficiently matches random graphs with inhomogeneous edge probabilities.

problem Matching latent vertex correspondence between two correlated random graphs with inhomogeneous edge probabilities.
method Inspired by Ding et al. (2021), an efficient matching algorithm is developed with conditions on minimal average degree and minimal correlation.
result An efficient matching algorithm is obtained as long as the minimal average degree is at least Ω(log2n)Ω(\log^{2} n) and the minimal correlation is at least 1O(log2n)1 - O(\log^{-2} n).

Unique inhomogeneous ruled hypersurface found in complex hyperbolic space.

problem Classifying ruled real hypersurfaces with constant norm.
method Analyzing nonflat complex space forms, proving existence and uniqueness.
result Existence of a unique inhomogeneous example in complex hyperbolic space.

Study optimal algorithms for recovering signals through inhomogeneous low-rank channels.

problem Recovering signals through an inhomogeneous low-rank matrix channel.
method Derive and analyze an approximate message-passing algorithm (AMP) and a spectral method.
result The AMP iteration matches the conjectured optimal computational phase transition.

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 ↗

Time homogeneous polynomial processes are Markov processes whose moments can be calculated easily through matrix exponentials. In this work, we develop a notion of time inhomogeneous polynomial processes where the coeffiecients of the process may depend on time. A full characterization of this model class is given by m…

2018-06-11abs ↗pdf ↗

We discuss several issues regarding material homogeneity and strain compatibility for materially uniform thin elastic shells from the viewpoint of a 3-dimensional theory, with small thickness, as well as a 2-dimensional Cosserat theory. A relationship between inhomogeneity and incompatibility measures under the two des…

2015-06-25abs ↗pdf ↗

Develops a new method for pricing barrier options in time-dependent Heston model.

problem Pricing barrier options in a time-dependent Heston model with stochastic volatility.
method General Integral Transforms (GIT) method for a two-dimensional integral representation.
result Shows that the GIT method can be extended to two drivers with inhomogeneous correlation.

We propose a scalable framework for inference in an inhomogeneous Poisson process modeled by a continuous sigmoidal Cox process that assumes the corresponding intensity function is given by a Gaussian process (GP) prior transformed with a scaled logistic sigmoid function. We present a tractable representation of the li…

2019-06-07abs ↗pdf ↗

We show how the relation between Poisson brackets and symplectic forms can be extended to the case of inhomogeneous multivector fields and inhomogeneous differential forms (or pseudodifferential forms). In particular we arrive at a notion which is a generalization of a symplectic structure and gives rise to higher Pois…

2008-08-25abs ↗pdf ↗

Proposes a new graph trend filtering model for inhomogeneous graph signals.

problem Estimating piecewise smooth signals over a graph with varying smoothness levels.
method Introduces a l2,0 norm penalized Graph Trend Filtering (GTF) model and two solution methods: spectral decomposition and simulated annealing.
result The GTF model performs better than existing approaches in denoising, support recovery, and semi-supervised classification.

This thesis is devoted to the study of affine processes and their applications in financial mathematics. In the first part we consider the theory of time-inhomogeneous affine processes on general state spaces. We present a concise setup for time-inhomogeneous Markov processes. For stochastically continuous affine proce…

2015-12-10abs ↗pdf ↗

This research provides theoretical guarantees for hyperparameter estimation in complex network dynamical systems.

problem Theoretical guarantees for hyperparameter estimation in large, inhomogeneous complex network dynamical systems.
method Formulating the system's evolution in a measure transport perspective, proposing a theoretical framework for estimating hyperparameters with mean-type observations.
result A nonasymptotic bound for the deviation of hyperparameter estimates in inhomogeneous complex network dynamical systems with respect to network population size.

We construct uncountably many isoparametric families of hypersurfaces in Damek-Ricci spaces. We characterize those of them that have constant principal curvatures by means of the new concept of generalized Kahler angle. It follows that, in general, these examples are inhomogeneous and have nonconstant principal curvatu…

2011-11-01abs ↗pdf ↗

Probabilistic proof of smooth boundaries in optimal stopping problems.

problem Continuous differentiability of time-dependent optimal boundaries in optimal stopping problems.
method Local probabilistic arguments for a wider range of conditions.
result First probabilistic proof of continuous differentiability under general conditions.

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.

Despite the fundamental nature of the inhomogeneous Poisson process in the theory and application of stochastic processes, and its attractive generalizations (e.g. Cox process), few tractable nonparametric modeling approaches of intensity functions exist, especially when observed points lie in a high-dimensional space.…

2016-10-27abs ↗pdf ↗

This paper develops methods for pricing American Parisian options under general Markov models.

problem Pricing American Parisian options with various types and payoff functions.
method General approaches using CTMC approximation for time-inhomogeneous Markov models, including state augmentation and variational inequalities.
result Efficient algorithms for pricing American Parisian options confirmed with numerical experiments.

A multi-task GP model tracks time-varying transition probabilities between two states.

problem Tracking time-varying transition probabilities between 'moves' and 'pauses' states.
method Kernel-based multi-task Gaussian Process model with time-variability and constraints.
result Enforces constraints while learning transition probabilities.

A new learning strategy using two GP layers for inhomogeneous data.

problem Addressing inhomogeneous empirical correlation structures in data.
method Modeling the function as a sample function of a non-stationary Gaussian Process (GP) nested within multiple stationary GPs, with hyperparameters dependent on the outer GP.
result The approach is sufficient with two GP layers, and the model can be implemented using MCMC.

Let P be a closed smooth (4j-2)-connected 8j-manifold. We complete Wilkens' classification of the manifolds P for j = 1,2 and give an alternative proof to Wall's classification of the manifolds for j > 2. The Hopf-invariant-one dimensions (j=1,2) are characteristed by the fact that the quadratic linking functions which…

2002-03-24abs ↗pdf ↗

Modeling aortic wall inhomogeneities to predict dissection risks.

problem Predicting localized stress accumulations in the aortic wall due to inhomogeneities.
method Stochastic constitutive model with random field realizations, coupled with a convolutional neural network surrogate.
result The neural network accurately predicts stress distributions and assesses uncertainty in aortic wall stress.