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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.

168,742 papers · 148 categories

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6.3%12.5%18.8%25.0% · Oct 199519922001200920172026
48 results for flow decomposition

The paper shows how gradient flow on over-parametrized tensor decomposition behaves like deflation.

problem Understanding the training dynamics of gradient flow on tensor decomposition.
method Empirical observation and mathematical proof of gradient flow dynamics for orthogonally decomposable tensors.
result Gradient flow dynamics for orthogonally decomposable tensors follows a tensor deflation process, recovering all tensor components.

The paper solves curvature problems on infinite hyperbolic surfaces.

problem Prescribed curvature flow on hyperbolic surfaces with infinite topological type.
method Introduced a prescribed curvature flow adapted to infinite cellular decompositions.
result Established well-posedness of the flow and proved convergence under certain conditions.

This paper uses combinatorial Ricci flow to tackle Thurston's triangulation conjecture.

problem Thurston's triangulation conjecture for hyperbolic 3-manifolds.
method Combinatorial Ricci flow approach to prove convergence and geometric decompositions.
result Combinatorial Ricci flow converges if and only if the triangulation is geometric.

Transverse one dimensional foliations play an important role in the study of codimension one foliations. In \cite{KR2}, the authors introduced the notion of flow box decomposition of a 3-manifold MM. This is a decomposition of MM that reflects both the structure of a given codimension one foliation and that of a give…

2016-05-10abs ↗pdf ↗

Develops methods to analyze feature-outcome associations in subpopulations.

problem Challenges in understanding feature-outcome associations in high-dimensional data.
method Geometric decomposition framework using gradient flow and co-monotonicity decomposition.
result Identifies context-dependent patterns and improves statistical power and interpretability.

The study connects geodesic flows on Riemann surfaces to random walks on their dual graphs.

problem Understanding ergodicity of geodesic flows on infinite Riemann surfaces.
method Analyzing random walks on the dual graph of pants decompositions.
result Equivalence between ergodicity of geodesic flows and recurrence of random walks.

Graph neural networks are explained through energy gradient flow and framelet decomposition.

problem Understanding and improving graph neural networks.
method Viewing framelet-based models as gradient flows of energy, proposing a generalized energy via framelet decomposition.
result The proposed model leads to more flexible dynamics, enhancing graph neural networks.

Unified framework for analyzing gradient flows of measures with exponential decay of entropy.

problem Analyzing exponential decay of entropy functionals in gradient flows of measures.
method Characterization of global exponential decay behaviors using Hellinger-Kantorovich geometry, shape-mass decomposition, and Polyak-Łojasiewicz-type inequalities.
result Unified theoretical framework for gradient flows with complete analysis of exponential decay behaviors.

We exhibit a concentration-collapse decomposition of singularities of fourth order curvature flows, including the L2L^2 curvature flow and Calabi flow, in dimensions n4n \leq 4. The proof requires the development of several new a priori estimates. First, we develop a smoothing result for initial metrics with small ener…

2013-11-05abs ↗pdf ↗

This paper explores vortices and harmonic flows on compact surfaces, using Hodge decomposition.

problem Understanding the interplay between vortices and harmonic flows on compact surfaces.
method Hodge decomposition of Euler's equations, focusing on point vortices on compact Riemann surfaces.
result The harmonic part of the flow is constant on flat tori but not on non-flat tori.

Geometry arising from two diffusion operators (smooth semi-elliptic, second order differential operators) on different spaces but intertwined by a smooth map is described. Particular cases arise from Riemannian submersions when the operators are Laplace-Beltrami operators, from equivariant operators on the total space …

2008-10-13abs ↗pdf ↗

Decompositions on manifolds appear in various geometric structures. Necessary and sufficient conditions for quotient spaces of decompositions to be manifolds are widely characterized. We characterize necessary and sufficient conditions to be kk-manifolds (k=1,2)(k = 1, 2), which generalize characterizations in the codimens…

2017-03-15abs ↗pdf ↗

Let S be a closed, connected, orientable surface of genus at least 2, and let C(S) denote the deformation space of convex real projective structures S. In this article, we introduce two new flows on C(S), which we call the internal bulging flow and the eruption flow. These are geometrically defined flows associated to …

2017-02-02abs ↗pdf ↗

We prove a uniform Sobolev inequality along the Sasaki-Ricci flow. In the process, we develop the theory of basic Lebesgue and Sobolev function spaces, and prove some general results about the decomposition of the heat kernel for a class of elliptic operators on a Sasaki manifold.

2011-04-06abs ↗pdf ↗

Study geometric flows of G2-structures, determining curvature and torsion invariants.

problem Investigate geometric flows of G2-structures and their invariants.
method Explicitly compute differential invariants, decompose curvature and torsion, analyze principal symbols.
result Established short-time existence and uniqueness for geometric flows of G2-structures.

Investigates nearly Kähler and parallel G2 manifolds using Hitchin functionals.

problem Stability analysis of nearly Kähler and parallel G2 manifolds.
method Gradient flow of Hitchin functionals, spectral decomposition of Hessians, Hitchin index.
result Hitchin index provides a lower bound for the Einstein co-index.

COMBO network improves optical flow estimation by combining deep learning with brightness constancy.

problem Optical flow estimation using deep learning requires complex training schemes.
method COMBO network explicitly exploits brightness constancy and combines it with a data-driven approach.
result COMBO network outperforms state-of-the-art methods on various benchmarks.

We make a conjecture about mean curvature flow of Lagrangian submanifolds of Calabi-Yau manifolds, expanding on \cite{Th}. We give new results about the stability condition, and propose a Jordan-Hölder-type decomposition of (special) Lagrangians. The main results are the uniqueness of special Lagrangians in hamiltonian…

2001-04-19abs ↗pdf ↗

In this paper we study the Föllmer-Schweizer decomposition of a square integrable random variable ξξ with respect to a given semimartingale SS under restricted information. Thanks to the relationship between this decomposition and that of the projection of ξξ with respect to the given information flow, we characteri…

2015-11-17abs ↗pdf ↗

Study infinite combinatorial Ricci flow on spherical surfaces.

problem Investigate infinite combinatorial Ricci flow with spherical background.
method Establish existence and convergence of solution for infinite cellular decompositions.
result Existence and convergence of solution for infinite combinatorial Ricci flow in spherical geometry.

HFNO enhances interpretability of turbulent flows through parallel wavenumber bin processing.

problem Opaque inner workings of Fourier Neural Operators (FNOs) hinder physical interpretability.
method Introduces HFNO, a novel FNO-based architecture that processes wavenumber bins in parallel, enhancing interpretability.
result HFNO decomposes turbulent flows across various scales, enabling increased interpretability and multiscale modeling.

A new method splits surface flow discretizations into streamfunctions and harmonic fields.

problem Discretizing incompressible flows on surfaces with pressure and saddle-point structure.
method Discrete Helmholtz-Hodge decomposition for BDM elements on surfaces.
result Eliminates pressure and saddle-point structure, ensuring exact tangentiality and divergence-freeness.

We propose a faster and more accurate method for learning classification trees.

problem Learning optimal binary classification trees is challenging and slow.
method We introduce a stronger MIP formulation and Benders' decomposition method.
result Our method is 50 times faster and improves out-of-sample performance.

Study controls bifurcations in Eulerian flows with multiple Hopf singularities.

problem Bifurcation analysis and control of nonlinear Eulerian flows with non-resonant n-tuple Hopf singularities.
method Analysis of CW complex bifurcations of flow-invariant Clifford hypertori, using leaf-bifurcation varieties.
result Tertiary toral CW complex bifurcates from and persists outside a secondary toral CW complex.

A flow-spine of a 3-manifold is a spine admitting a flow that is transverse to the spine, where the flow in the complement of the spine is diffeomorphic to a constant flow in an open ball. We say that a contact structure on a closed, connected, oriented 3-manifold is supported by a flow-spine if it has a contact form w…

2019-12-12abs ↗pdf ↗

We propose GraphNVP, the first invertible, normalizing flow-based molecular graph generation model. We decompose the generation of a graph into two steps: generation of (i) an adjacency tensor and (ii) node attributes. This decomposition yields the exact likelihood maximization on graph-structured data, combined with t…

2019-05-28abs ↗pdf ↗

We prove that the geodesic flow on the unit tangent bundle to a hyperbolic 2-orbifold is left-handed if and only if the orbifold is a sphere with three conic points. As a consequence, on the unit tangent bundle to a 3-conic sphere, the lift of every finite collection of closed geodesics that is zero in integral homolog…

2015-01-13abs ↗pdf ↗