A new method calculates fractional moments using the moment-generating function.
problem Computing fractional moments from probability densities.
method Integral framework based on moment-generating function.
result Exact integral expressions for various types of moments.
Gaussian process quadrature improves moment transformation accuracy.
problem Computing moments of transformed Gaussian variables with error accounting.
method Bayesian quadrature (Gaussian process quadrature) for numerically estimating integrals.
result Proposed method outperforms classical quadrature methods in accuracy.
This paper proves injectivity and support theorems for tensor fields on Riemannian manifolds.
problem Injectivity and support theorems for integral moments of m-tensor fields.
method Generalized Helgason's support theorem and used first m+1-integral moments of m-tensor fields.
result Injectivity and support theorems for integral moments of m-tensor fields.
For a finite-dimensional (but possibly noncompact) symplectic manifold with a compact group acting with a proper moment map, we show that the square of the moment map is an equivariantly perfect Morse function in the sense of Kirwan, and that the set of critical points of the square of the moment map is a countable dis…
Deform quantization recovers scalar curvature in complex structures.
problem Recovering scalar curvature in complex structures.
method Formal moment map construction on almost complex structures.
result Formal moment map deforms scalar curvature moment map in integrable cases.
We study quantum moment maps of G-invariant star products, which are a quantum analogue of the moment map for classical Hamiltonian systems. Introducing an integral representation, we show that any quantum moment map for a G-invariant star product is differentiable. This property gives us a new method for the class…
Paper provides unbiased spectral moment estimates from finite data.
problem Challenges in estimating spectral moments from limited data.
method Dynamic programming approach to estimate spectral moments of kernel integral operator.
result Demonstrates consistency with theoretical spectra and practical utility in neural networks.
Comparison results for rough and non-rough Heston models, tighter bounds on moment explosion times.
problem Comparing Heston models with and without roughness.
method Comparison principle for non-linear Volterra integral equations.
result Tighter bounds on moment explosion times for rough Heston models.
Normal distributions ensure asymptotic variance reduction in moment matching Monte Carlo.
problem Asymptotic variance reduction in general integration problems.
method Characterization of conditions for asymptotic variance reduction using normal distributions.
result Asymptotic variance reduction is guaranteed for normal distributions in moment matching Monte Carlo.
This paper improves filtering of non-linear systems with heavy-tailed noise.
problem Improving filtering accuracy for non-linear systems with heavy-tailed noise.
method Developed a moment transformation for Student-t distributed random variables using Student-t process quadrature.
result The method outperforms state-of-the-art moment transforms in numerical examples.
Formula calculates higher moments of Siegel-Veech transform over Hecke triangle groups.
problem Computing higher moments of Siegel-Veech transform over specific groups.
method Geometric results and linear algebra to create integration formulas.
result Explicit integration formulas for densities of vector orbits.
The paper studies exponential functionals of processes with independent increments and their moments.
problem Analyzing the moments of exponential functionals of processes with independent increments.
method Deriving recurrent integral equations for Mellin transforms and applying them to calculate moments.
result Explicit formulas for the moments of It and I∞, and precise number of finite moments of I∞. The paper integrates quasi-Poisson manifolds into multiplicative D-valued moment maps.
problem Integrating quasi-Poisson manifolds into a broader geometric framework.
method Develops new aspects of shifted symplectic and Poisson geometry, establishing Lie-type correspondences and systematic constructions.
result Identifies multiplicative D-valued moment maps integrating quasi-Poisson manifolds, extending known constructions.
Calculates moments of sectional curvature on Riemannian manifolds.
problem Understanding the distribution and moments of sectional curvature.
method Integrating local Riemannian invariants and analyzing sectional curvature on Grassmann bundles.
result Proves a weak version of the Hitchin-Thorpe Inequality.
Generalizes moment-angle manifolds to arbitrary nice manifolds with corners.
problem Computing cohomology groups and rings for moment-angle manifolds.
method Stable decomposition, rim-cubicalization, partial diagonal maps, polyhedral product.
result Derived formulas for integral cohomology groups and rings of moment-angle manifolds.
The paper generalizes the moment map interpretation of scalar curvature in Kähler geometry.
problem Interpreting the variation of the Quillen metric in Kähler geometry.
method Constructing equivariant determinant line bundles and analyzing their curvature forms.
result The moment maps μj coincide with the Z-critical equations introduced by Dervan-Hallam. The paper generalizes a moment map interpretation of scalar curvature in Kähler geometry.
problem Interpreting scalar curvature as a moment map on the space of compatible almost complex structures.
method Constructing equivariant determinant line bundles and analyzing their curvature forms.
result The moment maps μj coincide with the Z-critical equations and generalize Fujiki's fiber integral formula. We establish a link between Archimedes' method of integration for calculating areas, volumes and centers of mass of segments of parabolas and quadrics of revolution by factorization via the moments of a balance and an integration technique for a particular integrable system, namely Bianchi's Bäcklund transformation for…
A new method for neural networks adapts to different domains without labeled data.
problem Adapting neural networks to new domains without labeled data.
method Metric-based regularization to maximize similarity of domain-specific activation distributions by aligning moments.
result The method achieves higher classification accuracies than existing approaches.
Let G be a complex reductive group and K a maximal compact subgroup. If X is a smooth projective G-variety, with a fixed (not necessarily integral) K-invariant Kaehler form, then the K-action is Hamiltonian. Let M be the zero fiber of the corresponding moment map. It is well known that the quotient M/K is a complex spa…
A Lie group G in a group pair (D,G), integrating a Lie algebra g in a Manin pair (d,g) has a quasi-Poisson structure. We define the quasi-Poisson actions of such Lie groups G, that generalize the Poisson actions of Poisson Lie groups. We define and study the moment maps for those quasi-Poisson actions which are quasi-h…
Paper characterizes equilibrium strategies for stochastic control with higher-order moments.
problem Stochastic control problems with higher-order moments.
method Novel characterization of time-consistent control problems, deriving equilibrium conditions via BSDEs.
result Derives sufficient and necessary conditions for an open-loop Nash equilibrium control (ONEC) in a novel way.
For a Hamiltonian, proper and free action of a Lie group G on a Dirac manifold (M,L), with a regular moment map μ:M→g∗, the manifolds M/G, μ−1(0) and μ−1(0)/G all have natural induced Dirac structures. If (M,L) is an integrable Dirac structure, we show that M/G is always integrable,…
Quantizes b-symplectic toric manifolds using T-modules.
problem Quantization of b-symplectic toric manifolds. method Bohr-Sommerfeld quantization via T-modules. result Dimension of quantization coincides with signed count of integral points in moment polytope.
New SGMM algorithm for efficient estimation of moment restriction models.
problem Estimation and inference on overidentified moment restriction models.
method Stochastic Approximation to Generalized Method of Moments (SGMM).
result SGMM offers fast and scalable implementation with streaming dataset handling.
The paper proves localization formulas for contact manifolds.
problem Localization of integrals on contact manifolds.
method Equivariant basic cohomology and contact moment map.
result Analogue of localization formulas for contact manifolds.
In this paper we present a new methodology for option pricing. The main idea consists to represent a generic probability distribution function (PDF) via a perturbative expansion around a given, simpler, PDF (typically a gaussian function) by matching moments of increasing order. Because, as shown in literature, the pri…
In this note, we study the integral of the 1-form logxydy−logyxdx over certain plane curves defined by A-polynomials of knots. It is quite surprising that a Chern-Simons type invariant of 3-manifolds, which can be geometrically computed, may be used to get the exact values of those integrals. Th…
Study on quadratic L-functions using hyperelliptic curves and homology.
problem Understanding moments of families of quadratic L-functions.
method Homological stability theorem and computations of homology.
result Confirmations of Conrey-Farmer-Keating-Rubinstein-Snaith predictions for large prime powers.
Study connects surface classes to conservation laws.
problem Understanding CMC surfaces in space forms.
method Relates moment class to cohomology class, shows variational origin.
result Both classes have a variational origin as Noether currents.
Improved sigma-point filters reduce quadrature error bias.
problem Quadrature error in sigma-point filters leads to poorly calibrated estimates.
method Bayes-Sard quadrature method for sigma-point filters.
result Better-calibrated state estimates with improved RMSE.
In a recent significant advance, using Laguerre series, the valuation of Asian options has been reduced by Dufresne to computing the negative moments of Yor's accumulation processes. For these he has given functional recursion rules whose probabilistic structure has been the object of intensive recent studies of Yor an…
A novel method for learning DAGs from positive-valued data.
problem Causal discovery from observational data of positive-valued variables.
method Hybrid Moment-Ratio Scoring (H-MRS) algorithm combining moment-based scoring and log-scale regression.
result H-MRS integrates log-scale Ridge regression for moment-ratio estimation with a greedy ordering procedure based on raw-scale moment ratios, followed by Elastic Net-based parent selection.
A new filter reduces density fitting to a linear solve, improving performance on nonlinear systems.
problem Nonlinear Bayesian filtering challenges in representing belief distributions.
method Combines score matching with Stein's identity to avoid partition function evaluation.
result The Score Kalman Filter (SKF) outperforms existing methods on nonlinear systems.
Obstructions found for closed Fedosov star products on symplectic and Kähler manifolds.
problem Existence of closed Fedosov star products on symplectic and Kähler manifolds.
method Normalized trace of Fedosov star product, cohomology classes, and formal 2-forms.
result Integral invariants attached to symplectic and Kähler manifolds as obstructions to closed Fedosov star products.
Efficiently simulates SABR model with novel sampling methods.
problem Sampling integrated variance and terminal forward price in SABR model.
method Moment-matched shifted lognormal approximation for integrated variance, CEV approximation for terminal forward price.
result Enhanced simulation scheme is highly efficient, accurate, and reliable.
We relate stability properties (i.e. moment exponents) of a stochastic dynamical system on a compact manifold M to the homotopy and integral homology groups of M. In the special case of gradient Brownian systems associated to isometric immersions of M in Euclidean space, these moment exponents can be estimated in…
A new method extracts features and reconstructs moments in dynamical systems using information geometry.
problem Reconstructing moments in dynamical systems efficiently and accurately.
method Information-geometric approach on spaces of probability measures.
result Moments can be expanded in eigenfunctions of a kernel integral operator, enabling nonparametric forecasting.
New method calculates tail probabilities of compound heavy-tailed distributions.
problem Computing tail probabilities of compound distributions with heavy tails.
method Contour integration method to represent tail probability as a rapidly convergent integral.
result Viable alternative to Monte Carlo and FFT methods for high percentile levels.
New method approximates MMD using pseudo-differential operators and singular values.
problem Approximating MMD with pseudo-differential operators and singular values.
method Corresponding pseudo-differential operators to Mercer kernels, approximating p(x,y) with its first r singular values. result The new MMD distance measures the difference of two distributions with respect to r∗ local moments, where r∗ depends on singular values decay rate. In many statistical problems, a more coarse-grained model may be suitable for population-level behaviour, whereas a more detailed model is appropriate for accurate modelling of individual behaviour. This raises the question of how to integrate both types of models. Methods such as posterior regularization follow the id…
DualAdam improves generalization of Adam by integrating its update mechanisms.
problem Adam's tendency to converge to sharp minima leading to suboptimal generalization.
method DualAdam combines Adam and inverse Adam's update mechanisms to enhance generalization.
result DualAdam outperforms Adam and state-of-the-art variants in generalization performance.
We show that the cone associated with a moment map for an action of a torus on a contact compact connected manifold is a convex polyhedral cone and that the moment map has connected fibers provided the dimension of the torus is bigger than 2 and that no orbit is tangent to the contact distribution. This may be consider…
We consider symplectic manifolds with Hamiltonian torus actions which are "almost but not quite completely integrable": the dimension of the torus is one less than half the dimension of the manifold. We provide a complete set of invariants for such spaces when they are "centered" and the moment map is proper. In partic…
The paper proposes a method to estimate complex models using machine learning.
problem Estimating the impact of welfare reform on women's welfare participation.
method Regularized orthogonal machine learning for non-linear semiparametric models.
result The proposed Lasso estimator converges at the oracle rate, preserving the single index property.
We analyze exponential integrability properties of the Cox-Ingersoll-Ross (CIR) process and its Euler discretizations with various types of truncation and reflection at 0. These properties play a key role in establishing the finiteness of moments and the strong convergence of numerical approximations for a class of sto…
The paper establishes criteria for approximating processes to match moments, useful for enriching data with simulated data.
problem Ensuring approximating processes match moments for data enrichment.
method Generalizes criteria for approximating processes to match moments, extending to random fields of stochastic processes.
result Uniform integrability is sufficient for matching moments, even for processes under weak stationarity.
In this paper we apply Donaldson's general moment map framework for the action of a symplectomorphism group on the corresponding space of compatible (almost) complex structures to the case of rational ruled surfaces. This gives a new approach to understanding the topology of their symplectomorphism groups, based on a r…