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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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18375573 · Jun 202619922001200920172026
48 results for strange identities

Andrews and Sellers recently initiated the study of arithmetic properties of Fishburn numbers. In this paper, we prove prime power congruences for generalized Fishburn numbers. These numbers are the coefficients in the 1q1-q expansion of the Kontsevich-Zagier series Ft(q)\mathscr{F}_{t}(q) for the torus knots T(3,2t)T(3,2^t), …

2020-02-03abs ↗pdf ↗

In this paper we study the Lorenz equations using the perspective of the Conley index theory. More specifically, we examine the evolution of the strange set that these equations posses throughout the different values of the parameter. We also analyze some natural Morse decompositions of the global attractor of the syst…

2018-12-12abs ↗pdf ↗

Recently V. Arnold introduced Strangeness and J±J^{\pm} invariants of generic immersions of an oriented circle to R2\R^2. Here these invariants are generalized to the case of generic immersions of an oriented circle to an arbitrary surface FF. We explicitly describe all the invariants satisfying axioms, which naturall…

1999-06-18abs ↗pdf ↗

Experimental measurements of physical systems often have a limited number of independent channels, causing essential dynamical variables to remain unobserved. However, many popular methods for unsupervised inference of latent dynamics from experimental data implicitly assume that the measurements have higher intrinsic …

2020-02-14abs ↗pdf ↗

Quantum modularity proved for a knot manifold.

problem Proving quantum modularity for a specific closed hyperbolic 3-manifold.
method Using factorization of state integrals and proving quantum modularity for functions and qq-series.
result Quantum modularity for the closed manifold provides a unification of volume conjecture and Witten's asymptotic expansion conjecture.

We investigate the issue of model selection and the use of the nonconformity (strangeness) measure in batch learning. Using the nonconformity measure we propose a new training algorithm that helps avoid the need for Cross-Validation or Leave-One-Out model selection strategies. We provide a new generalisation error boun…

2009-09-12abs ↗pdf ↗

It is shown that a lagrangian system whose Legendre transformation degenerates along a hypersurface behaves in a strange manner by jumping from time to time without any ''visible cause''. In such a jump the system changes instantaneously its coordinates as well as its momenta. The mathematical dscription of the phenome…

1999-02-19abs ↗pdf ↗

The use of artificial neural networks as models of chaotic dynamics has been rapidly expanding. Still, a theoretical understanding of how neural networks learn chaos is lacking. Here, we employ a geometric perspective to show that neural networks can efficiently model chaotic dynamics by becoming structurally chaotic t…

2019-12-11abs ↗pdf ↗

Following \cite{citeSavelyevVirtualMorsetheoryonOmegaOmegaHam(Momega)(Momega).}, we develop here a connection between Morse theory for the (positive) Hofer length functional L:ΩHam(M,ω)RL: Ω\text {Ham}(M, ω) \to \mathbb{R}, with Gromov-Witten/Floer theory, for monotone symplectic manifolds (M,ω) (M, ω) . This gives some immediate restrictio…

2013-08-15abs ↗pdf ↗

Study discrete analog of zeta-determinant maximization on triangulated surfaces.

problem Maximizing zeta-determinant for discrete Laplacian on triangulated surfaces.
method Analogous to Osgood, Phillips, and Sarnak's theorem, study stationary points of determinants for discrete cotan-Laplacian.
result Discrete metrics of constant discrete Gaussian curvature are stationary points of the determinant, suggesting minima.

The literature postulates that the dynamic time warping (dtw) distance can cope with temporal variations but stores and processes time series in a form as if the dtw-distance cannot cope with such variations. To address this inconsistency, we first show that the dtw-distance is not warping-invariant. The lack of warpin…

2019-03-04abs ↗pdf ↗

This paper discovers new identities linking geodesic and orthogeodesic lengths on hyperbolic surfaces.

problem Understanding relationships between geodesic and orthogeodesic lengths on hyperbolic surfaces.
method Investigates a broad family of identities involving lengths of all closed geodesics and orthogeodesics.
result Introduces new identities that include lengths of all closed geodesics, contrasting with previous identities.

Let (M,g)(M,g) be a compact manifold and let Δφk=λkφk-Δφ_k = λ_k φ_k be the sequence of Laplacian eigenfunctions. We present a curious new phenomenon which, so far, we only managed to understand in a few highly specialized cases: the family of functions fN:MR0f_N:M \rightarrow \mathbb{R}_{\geq 0} $$ f_N(x) = \sum_{k \leq N}{ \frac{…

2017-06-05abs ↗pdf ↗

Bayesian Neural Networks improve uncertainty modeling in facial emotion recognition.

problem High aleatoric uncertainty and visual ambiguity in facial emotion recognition.
method Bayesian Neural Networks approximated using MC-Dropout, MC-DropConnect, or Ensemble methods.
result Bayesian Neural Networks produce more human-like output probabilities.

100 years ago exactly, in 1906, Hartogs published a celebrated extension phenomenon (birth of Several Complex Variables), whose global counterpart was stated in full generality later by Osgood (1929): holomorphic functions in a connected neighborhood V(bD) of a connected boundary bD contained in C^n (n >= 2) do extend …

2006-10-31abs ↗pdf ↗

Quandle homology was defined from rack homology as the quotient by a subcomplex corresponding to the idempotency, for invariance under the type I Reidemeister move. Similar subcomplexes have been considered for various identities of racks and moves on diagrams. We observe common aspects of these identities and subcompl…

2016-02-27abs ↗pdf ↗

The paper derives curvature identities for 5D and 6D Einstein manifolds.

problem Deriving curvature identities for specific dimensions of Einstein manifolds.
method Using Patterson's curvature identities and the Chern-Gauss-Bonnet Theorem, the paper provides explicit formulae for 5D and 6D Einstein manifolds.
result The curvature identities for 5D and 6D Einstein manifolds are confirmed to be consistent with previous work.

Study shows Lefschetz fibrations on Milnor fibers of certain singularities.

problem Understanding Lefschetz fibrations on Milnor fibers of specific singularities.
method Analyzes Milnor fibers of cusp and simple elliptic singularities to construct Lefschetz fibrations.
result Milnor fibers of cusp and simple elliptic singularities admit genus-one Lefschetz fibrations.

User identity linkage is a task of recognizing the identities of the same user across different social networks (SN). Previous works tackle this problem via estimating the pairwise similarity between identities from different SN, predicting the label of identity pairs or selecting the most relevant identity pair based …

2019-10-31abs ↗pdf ↗

In our previous paper (Axiomatic Differential Geometry II-3) we have discussed the general Jacobi identity, from which the Jacobi identity of vector fields follows readily. In this paper we derive Jacobi-like identities of tangent-vector-valued forms from the general Jacobi identity.

2012-11-22abs ↗pdf ↗

We give a curvature identity derived from the generalized Gauss-Bonnet formula for 4-dimensional compact oriented Riemannian manifolds. We prove that the curvature identity holds on any 4-dimensional Riemannian manifold which is not necessarily compact. We also provide some applications of the identity.

2010-08-14abs ↗pdf ↗

Proposes a new method combining Reservoir Computing and Normalizing Flow for predicting stochastic dynamical systems.

problem Predicting and capturing long-term behaviors of stochastic dynamical systems.
method Data-driven framework combining Reservoir Computing and Normalizing Flow, integrating error modeling and both approaches virtues.
result Successfully predicts the long-term evolution of stochastic dynamical systems and replicates dynamical behaviors.