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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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129259388517 · Jun 202019922001200920172026
48 results for universal mapping property

Narasihman and Ramanan proved that an arbitrary connection in a vector bundle over a base space B can be obtained as the pull-back (via a correctly chosen classifying map from B into the appropriate Grassmannian) of the universal connection in the universal bundle over the Grassmannian. The purpose of this paper is to …

2014-05-27abs ↗pdf ↗

Universal approximation for ODENet and ResNet with a single activation function.

problem Approximating complex dynamical systems with limited vector fields.
method Examined ODENet and ResNet with vector fields composed of a single activation function and affine mapping.
result ODENet and ResNet with restricted vector fields can uniformly approximate those with general vector fields.

NODEs can approximate a wide range of diffeomorphisms with strong guarantees.

problem The approximation power of NODEs under certain conditions.
method Leveraging a structure theorem of the diffeomorphism group.
result NODEs can approximate a large class of diffeomorphisms with a stronger guarantee.

The aim of this paper is to introduce the concepts of homotopical smallness and closeness. These are the properties of homotopical classes of maps that are related to recent developments in homotopy theory and to the construction of universal covering spaces for non-semilocally simply connected spaces, in particular to…

2011-01-04abs ↗pdf ↗

For several instances of metric largeness like enlargeability or having hyperspherical universal covers, we construct non-large vector subspaces in the rational homology of finitely generated groups. The functorial properties of this construction imply that the corresponding largeness properties of closed manifolds dep…

2009-02-05abs ↗pdf ↗

Quantum machine learning models can approximate any continuous function.

problem Theoretical understanding of quantum feature maps in machine learning.
method Proving universal approximation property of quantum machine learning models in quantum-enhanced feature spaces.
result Quantum machine learning models are universal approximators of continuous functions.

Path signatures adapted for Lie groups improve action recognition in computer vision.

problem Improving action recognition in computer vision with geometric constraints.
method Lifting path signatures to Lie groups and proving universality and characteristic property.
result Path signatures on Lie groups provide comparable performance to shallow learning approaches in action recognition.

Starting from an arbitrary sequence of polygons whose total perimeter is 2n2n, we can build an (oriented) surface by pairing their sides in a uniform fashion. Chmutov and Pittel (arXiv:1503.01816) have shown that, regardless of the configuration of polygons we started with, the degree sequence of the graph obtained thi…

2019-02-04abs ↗pdf ↗

Dimension reduction is the process of embedding high-dimensional data into a lower dimensional space to facilitate its analysis. In the Euclidean setting, one fundamental technique for dimension reduction is to apply a random linear map to the data. This dimension reduction procedure succeeds when it preserves certain …

2015-11-30abs ↗pdf ↗

We present effective methods to compute equivariant harmonic maps from the universal cover of a surface into a nonpositively curved space. By discretizing the theory appropriately, we show that the energy functional is strongly convex and derive convergence of the discrete heat flow to the energy minimizer, with explic…

2018-10-29abs ↗pdf ↗

Real blow-up, including inhomogeneous versions, of boundary faces of a manifold (with corners) is an important tool for resolving singularities, degeneracies and competing notions of homogeneity. These constructions are shown to be particular cases of `generalized boundary blow-up' in which a new manifold and blow-down…

2011-07-17abs ↗pdf ↗

We extend the notion of an almost flat bundle over a closed Riemannian manifold to bundles over simplicial complexes, and prove that up to a constant factor, this notion is invariant under pullback via maps which induce isomorphisms on fundamental groups. As an application, we show that the property of having infinite …

2016-07-26abs ↗pdf ↗

The paper shows that for Coxeter groups, the commensurator of outer automorphisms is rigid.

problem The rigidity of commensurator of outer automorphisms of Coxeter groups.
method Study of the abstract commensurator of the outer automorphism group of a universal Coxeter group.
result For n5n \geq 5, the natural map is an isomorphism and every isomorphism between finite index subgroups is conjugation.

Unified method for CNNs to approximate equivariant maps across various groups.

problem Limited universal approximation theorems for CNNs with specific groups and settings.
method Unified approach to derive universal approximation theorems for equivariant maps by CNNs in diverse settings.
result Ability to handle non-linear equivariant maps between infinite-dimensional spaces for non-compact groups.

Study geometric properties of log Calabi-Yau manifolds, focusing on Fano manifolds with smooth or two proportional components.

problem Geometric properties of log Calabi-Yau manifolds in two specific cases.
method Analysis of various geometric properties, focusing on Bochner principle, local triviality, polystability, and compactifiability of universal cover.
result The universal cover of XDX\setminus D is a Calabi-Yau manifold of infinite topological type when DD has two components.

We prove the universal lifting theorem: for an αα-simply connected and αα-connected Lie groupoid $\gm$ with Lie algebroid AA, the graded Lie algebra of multi-differentials on AA is isomorphic to that of multiplicative multi-vector fields on $\gm$. As a consequence, we obtain the integration theorem for a quasi-Lie …

2005-07-19abs ↗pdf ↗

We study the approximation properties of random ReLU features through their reproducing kernel Hilbert space (RKHS). We first prove a universality theorem for the RKHS induced by random features whose feature maps are of the form of nodes in neural networks. The universality result implies that the random ReLU features…

2018-10-10abs ↗pdf ↗

This short review is the result of a minicourse at the Sapienza University of Rome the author gave about the proof of the gg-theorem. We review the hard Lefschetz theorem for simplicial spheres, as well as the theory at its core: perturbations of maps, biased Poincaré pairings and a cobordism argument that relates the…

2019-06-14abs ↗pdf ↗

New proof shows incremental flow models are essential for universal generation.

problem Understanding the universality of flow-based models in generating natural maps.
method Topological-dynamical argument and algebraic properties of flows.
result Incremental generation is necessary and sufficient for universal flow-based generation.

The paper defines a condition for the finiteness of mapping class groups of Heegaard splittings.

problem Conditions for the finiteness of mapping class groups of Heegaard splittings.
method Use of the thick isotopy lemma to establish conditions for finiteness.
result Heegaard splittings with topologically minimal disk complex and finitely generated homotopy group have finitely generated mapping class groups.

We introduce a new feature map for barcodes that arise in persistent homology computation. The main idea is to first realize each barcode as a path in a convenient vector space, and to then compute its path signature which takes values in the tensor algebra of that vector space. The composition of these two operations …

2018-06-01abs ↗pdf ↗

Metric spaces with certain curvature properties are universally infinitesimally Hilbertian.

problem Analyzing the infinitesimal geometry of metric spaces with curvature bounds.
method Proving a metric space with a Gromov-Hausdorff tangent splitting property is universally infinitesimally Hilbertian.
result Metric spaces with curvature bounds are universally infinitesimally Hilbertian.

Generalizes neural network approximation to infinite-dimensional manifolds and derivatives.

problem Approximating differentiable maps on infinite-dimensional manifolds.
method Proves a weighted Nachbin theorem to establish universal approximation for differentiable maps, including derivatives.
result Linear functions of the signature can approximate path space functionals including their derivatives.

Learning three data points can generate all types of periodic orbits in a neural network.

problem Can learning three data points generate all types of periodic orbits in a neural network?
method Investigated a continuous one-dimensional map with period three in a random neural network in its thermodynamic limit.
result Almost all learned periods are unstable, and each network has its own characteristic attractors.

A basic problem in machine learning is to find a mapping ff from a low dimensional latent space Y\mathcal{Y} to a high dimensional observation space X\mathcal{X}. Modern tools such as deep neural networks are capable to represent general non-linear mappings. A learner can easily find a mapping which perfectly fits a…

2018-11-05abs ↗pdf ↗

We record various properties of twisted Becker-Gottlieb transfer maps and study their multiplicative properties analogous to Becker-Gottlieb transfer. We show these twisted transfer maps factorise through Becker-Schultz-Mann-Miller-Miller transfer; some of these might be well known. We apply this to show that $BSO(2n+1…

2014-07-27abs ↗pdf ↗