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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.

169,291 papers · 148 categories

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66132198264 · Jun 202019922001200920182026
48 results for Tensor Maximum Principle

Study of asymmetric rank-one tensor models with non-Gaussian noise.

problem Analyzing maximum-likelihood estimators for asymmetric rank-one tensor models.
method Spectrally separated branch analysis, resolvent methods, cumulant expansions, Efron-Stein-type variance bounds.
result Asymptotic singular value and mode-wise alignments are robust to non-Gaussian noise.

The paper studies a heat flow for diffeomorphisms on flat surfaces, preserving their structure.

problem Studying a specific heat flow equation on flat surfaces.
method Using a tensor maximum principle and a change of variables, the authors establish bounds and regularity results.
result The heat flow preserves diffeomorphisms, unlike harmonic map heat flow.

Compact Kähler spaces with zero first Chern class have special geometric properties.

problem Characterizing Kähler spaces with zero first Chern class.
method Analyzing holomorphic tensors, decomposing tangent sheaf, and using Bochner principle.
result Spaces with zero first Chern class split off a complex torus and have specific holonomy representations.

We consider the four-dimensional nonholonomic distribution defined by the 4-potential of the electromagnetic field on the manifold. This distribution has a metric tensor with the Lorentzian signature (+,,,)(+,-,-,-), therefore, the causal structure appears as in the general relativity theory. By means of the Pontryagin's m…

2007-06-21abs ↗pdf ↗

The paper establishes a version of the Hopf boundary point lemma for sections of a vector bundle over a manifold with boundary. This result may be viewed as a counterpart to the tensor maximum principle obtained by R. Hamilton in 1986. Potential applications include the study of various geometric flows and the construc…

2006-08-01abs ↗pdf ↗

The paper establishes maximum principles and stochastic completeness for pseudo-Hermitian manifolds.

problem Maximum principles and stochastic completeness for pseudo-Hermitian manifolds.
method Established generalized maximum principles and proved stochastic completeness equivalence.
result Stochastic completeness for the heat semigroup is equivalent to generalized maximum principles.

Study on 4D Ricci solitons with specific curvature properties.

problem Characterizing 4D complete gradient shrinking Ricci solitons with half positive isotropic curvature.
method Curvature estimates, strong maximum principle, classification arguments.
result New classification results for gradient shrinking Kähler-Ricci solitons and 4D complete gradient shrinking Ricci solitons with half nonnegative isotropic curvature.

We present a new statistical learning paradigm for Boltzmann machines based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from Jaynes maximum entropy principle and from standard maximum likelihood estimation.We demonstrate the LME principle BY deriving …

2012-10-19abs ↗pdf ↗

Study extends ODE Maximum Principle to non-compact hypersurfaces in hyperbolic space.

problem Analyzing long-term behavior of IMCF on non-compact hypersurfaces.
method Extends ODE Maximum Principle to non-compact hypersurfaces using Omari-Yau maximum principle at infinity.
result Showed long-time existence and asymptotic convergence of IMCF to horospheres.

In this paper we characterize the degenerate elliptic equations F(D^2u)=0 whose viscosity subsolutions, (F(D^2u) \geq 0), satisfy the strong maximum principle. We introduce an easily computed function f(t) for t > 0, determined by F, and we show that the strong maximum principle holds depending on whether the integral …

2013-09-06abs ↗pdf ↗

Study on maximum principles for nonlinear equations on Riemannian manifolds.

problem Investigating strong maximum principles for fully nonlinear equations on Riemannian manifolds.
method Analyzing scaling conditions and applying to various nonlinear operators.
result Established new strong comparison principles for second order uniformly elliptic problems.

Study strong maximum principles for mean curvature operators on subriemannian manifolds.

problem Investigate strong maximum principles for mean curvature operators on subriemannian manifolds.
method Analyze subriemannian manifolds including Heisenberg groups and cylinders, under Hormander type conditions.
result Show strong maximum principles for horizontal (p-) mean curvature operator and p-(sub)laplacian operator under certain conditions.

In this work we consider viscosity solutions to second order partial differential equations on Riemannian manifolds. We prove maximum principles for solutions to Dirichlet problem on a compact Riemannian manifold with boundary. Using a different method, we generalize maximum principles of Omori and Yau to a viscosity v…

2008-06-29abs ↗pdf ↗

This article studies a discrete geometric structure on triangulated manifolds and an associated curvature flow (combinatorial Yamabe flow). The associated evolution of curvature appears to be like a heat equation on graphs, but it can be shown to not satisfy the maximum principle. The notion of a parabolic-like operato…

2002-11-13abs ↗pdf ↗

Extends variational principle to tensor Banach spaces.

problem High-dimensional partial differential equations and minimization problems.
method Describes tensor product as disjoint connected components, each modeled as a Banach manifold.
result Extension of Dirac-Frenkel variational principle to topological tensor spaces.

New principle for harmonic maps helps study higher-dimensional submanifolds.

problem Understanding unboundedness of totally geodesic projections in higher codimension.
method Introducing a flexible notion of convexity and applying it to harmonic and conformal maps.
result New maximum principle for harmonic maps applicable to various geometric settings.

Study compares nodal sets of solutions to the Allen-Cahn equation.

problem Comparing nodal sets of solutions to the Allen-Cahn equation with conical asymptotics.
method Maximum principle for linearized operator on unbounded domains.
result Positive phase uniquely determines the solution and enforces global ordering.

Ancient Ricci flows with bounded girth found in 3D and higher.

problem Finding ancient Ricci flows with bounded girth in dimensions 3 and higher.
method Invariant conditions on curvature and its derivatives under O(2)imesO(n1)O(2) imes O(n-1) symmetry, proving Ricci flow invariance.
result Construction of new ancient Ricci flows with positive curvature operator and bounded girth.

According to a classical result of E.~Calabi any hyperbolic affine hypersphere endowed with its natural Hessian metric has a non-positive Ricci tensor. The affine hyperspheres can be described as the level sets of solutions to the "hyperbolic" toric Kähler-Einstein equation eΦ=detD2Φe^Φ = \det D^2 Φ on proper convex cones. We…

2016-04-14abs ↗pdf ↗

We consider geometric flow equations for contracting and expanding normal velocities, including powers of the Gauss curvature, of the mean curvature, and of the norm of the second fundamental form, and ask whether - after appropriate rescaling - closed strictly convex surfaces converge to spheres. To prove this, many a…

2015-01-28abs ↗pdf ↗

Pontryagin's Maximum Principle is an outstanding result for solving optimal control problems by means of optimizing a specific function on some particular variables, the so called controls. However, this is not always enough for solving all these problems. A high order maximum principle (Krener, 1977) must be used in o…

2012-10-25abs ↗pdf ↗

Proposes a new method for high-dimensional density estimation.

problem Estimating high-dimensional probability density functions efficiently.
method Tensorizing flow method combining tensor-train and flow-based generative modeling.
result Efficiently constructs an approximate density in tensor-train form and trains a flow model to match empirical distribution.

MEP-Net uses MEP to generate solutions from limited data.

problem Generating solutions to scientific problems with incomplete information.
method Combines MEP with neural networks to learn complex distributions from moment constraints.
result Demonstrates MEP-Net's effectiveness in modeling biochemical reaction networks and generating complex distributions.

A novel Laplace-approximated Bayesian Tensor Network Kernel Machine (LA-TNKM) provides principled uncertainty estimates.

problem How to provide principled uncertainty estimates for tensor network kernel machines.
method Employing a linearized Laplace approximation for Bayesian inference.
result Consistently matches or surpasses Gaussian Processes and BNNs across diverse UCI regression benchmarks.