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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.

168,657 papers · 148 categories

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141283424565 · Jun 202019922001200920172026
48 results for Embedding Spaces

Isometric embeddings of Teichmüller spaces are derived from branched coverings.

problem Characterizing isometric embeddings of Teichmüller spaces.
method Holomorphic isometric embeddings induced by branched coverings.
result All isometric embeddings of Teichmüller spaces of dimension at least 2 arise from branched coverings.

We obtain multirelative connectivity statements about spaces of Poincare embeddings, as precursors to analogous statements about spaces of smooth embeddings. The latter are the key to convergence results in the functor calculus approach to spaces of embeddings.

2008-01-25abs ↗pdf ↗

Study rational homotopy types of embedding spaces of manifolds.

problem Understanding the rational homotopy types of embedding spaces of manifolds.
method Express rational homotopy types through combinatorially defined L-infinity algebras of diagrams.
result Expressed the rational homotopy type of connected components of embedding spaces.

Paper explores coarse embeddings between symmetric spaces and Euclidean buildings, answering open questions.

problem Understanding coarse embeddings between symmetric spaces and Euclidean buildings.
method Generalization of quasi-isometric embeddings, focusing on coarse embeddings without Euclidean factors.
result Rank is monotonous under coarse embeddings when the domain does not contain a Euclidean factor.

Study explores embedding signature-changing manifolds into higher-dimensional spaces.

problem Smooth metric signature changes in spacetimes.
method Global isometric embeddings into higher-dimensional pseudo-Euclidean spaces.
result Explicit constructions of global embeddings into Minkowski and Misner spaces.

Research explores the space-like embeddings in pseudo-hyperbolic space, finding geometric frames and actions.

problem Flat maximal space-like embeddings in pseudo-hyperbolic space.
method Description of Codazzi tensors, introduction of pseudo-Kähler metrics, Hamiltonian actions, moment maps, and geometric frames.
result Existence of two Hamiltonian actions with moment maps and geometric global Darboux frame.

Maps and embeddings between hyperbolic spaces and their boundaries studied.

problem Understanding relations between maps and embeddings between relatively hyperbolic spaces and their boundaries.
method Establishing correspondences between quasi-isometric embeddings and quasisymmetric embeddings, using polynomial distortion.
result Characterization of hyperbolic relative groups with polynomial distortion embeddings.

Contrastive embeddings improve neural architecture search performance.

problem Improving performance of neural architecture search algorithms.
method Contrastive learning to identify networks based on data Jacobians and produce embeddings.
result Traditional black-box optimization algorithms can reach state-of-the-art performance with contrastive embeddings.

We prove that every proper nn-dimensional length metric space admits an "approximate isometric embedding" into Lorentzian space R3n+6,1\mathbb{R}^{3n+6,1}. By an "approximate isometric embedding" we mean an embedding which preserves the energy functional on a prescribed set of geodesics connecting a dense set of points.

2016-01-28abs ↗pdf ↗

Euclidean embeddings of data are fundamentally limited in their ability to capture latent semantic structures, which need not conform to Euclidean spatial assumptions. Here we consider an alternative, which embeds data as discrete probability distributions in a Wasserstein space, endowed with an optimal transport metri…

2019-05-08abs ↗pdf ↗

This paper tightens the generalization error bound for graph embedding in non-Euclidean spaces.

problem High generalization error in non-Euclidean graph embedding, preventing practical applications.
method Novel upper bound of graph embedding's generalization error using local Rademacher complexity.
result The new bound is tighter and faster, allowing better performance in non-Euclidean spaces.

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The success of neural embeddings has prompted significant amounts of research into appli…

2017-05-29abs ↗pdf ↗

The notion of ideal embeddings was introduced in [B.-Y. Chen, {Strings of Riemannian invariants, inequalities, ideal immersions and their applications.} The Third Pacific Rim Geometry Conference (Seoul, 1996), 7-60, Int. Press, Cambridge, MA, 1998]. Roughly speaking, an ideal embedding (or a best of living) is an isome…

2017-06-20abs ↗pdf ↗

We prove that each sub-Riemannian manifold can be embedded in some Euclidean space preserving the length of all the curves in the manifold. The result is an extension of Nash C1C^1 Embedding Theorem. For more general metric spaces the same result is false, e.g., for Finsler non-Riemannian manifolds. However, we also sh…

2010-05-10abs ↗pdf ↗

Study of embedding spaces using homotopy theory and operads.

problem Understanding the stable homotopy type of embedding spaces.
method Analysis of cubes of framed configuration spaces, homotopy theory of presheaves, operadic structures.
result Induced action of the Poisson operad on the homology of configuration spaces is a homotopy invariant.

AMES framework selects optimal embedding space for latent graph inference.

problem No principled method for choosing the best embedding space for latent graph inference.
method Differentiable AMES framework using backpropagation to select optimal embedding space.
result Consistently achieves comparable or superior results across multiple datasets.

Paper addresses hidden faces in configuration space integrals for embeddings.

problem Understanding hidden faces in configuration space integrals for long embeddings.
method Modified configuration space integrals incorporating acyclic bar complex of a dg algebra.
result Cochain map from new graph complex to de Rham complex of embeddings modulo immersions.

The Farey tree helps embed rational balls and lens spaces into complex projective space.

problem Embedding rational homology balls and lens spaces into complex projective space.
method Recursive Kirby calculus argument using the Farey tree.
result Explicit constructions of embeddings of triples of rational homology balls into homotopy CP2\mathbb{CP}^2.

Long spacelike embeddings can be approximated by isometric ones.

problem Approximating long embeddings to isometric embeddings in Lorentzian spaces.
method Proving approximation by constructing C1C^1 isometric embeddings.
result Long spacelike embeddings can be C0C^0-approximated by C1C^1 isometric embeddings.

Curvature regularization prevents distortion in graph embeddings.

problem Graph topology patterns distort in Euclidean space, making detection difficult.
method Proposes curvature regularization to enforce flatness in embedding manifolds.
result Significant improvements in five embedding methods on open graph datasets.

Paper proves embedding theorem for conformally compact manifolds.

problem Embedding conformally compact manifolds into hyperbolic spaces.
method Proves analogous Nash Embedding Theorem for conformally compact manifolds.
result Conformally compact manifolds can be isometrically embedded into hyperbolic spaces.

We show that a pseudo-holomorphic embedding of an almost-complex 2n2n-manifold into almost-complex (2n+2)(2n + 2)-Euclidean space exists if and only if there is a CR regular embedding of the 2n2n-manifold into complex (n+1)(n + 1)-space. We remark that the fundamental group does not place any restriction on the existence of e…

2018-04-21abs ↗pdf ↗

New method learns state embeddings from demonstrations for improved reinforcement learning.

problem Difficult relationship between observed state and useful policy actions in dynamic problems.
method Variational framework for learning state embeddings that optimize trajectory linearity.
result Learning embedding spaces improves policy gradient reinforcement learning performance.

The study characterizes and verifies equivariant embeddings of symmetric Kählerian manifolds.

problem Characterizing and verifying equivariant embeddings of symmetric Kählerian manifolds.
method Investigation motivated by Cartan and Wallach's theorem on symmetric spaces, focusing on CPn\mathbb{CP}^n and parallel plurimean curvature.
result If an equivariant embedding has parallel plurimean curvature, it is the extrinsically symmetric one.

We show that, for a closed orientable n-manifold, with n not congruent to 3 modulo 4, the existence of a CR-regular embedding into complex (n-1)-space ensures the existence of a totally real embedding into complex n-space. This implies that a closed orientable (4k+1)-manifold with non-vanishing Kervaire semi-characteri…

2018-03-22abs ↗pdf ↗

We announce results about flat (linkless) embeddings of graphs in 3-space. A piecewise-linear embedding of a graph in 3-space is called {\it flat} if every circuit of the graph bounds a disk disjoint from the rest of the graph. We have shown: (i) An embedding is flat if and only if the fundamental group of the compleme…

1993-01-01abs ↗pdf ↗

The paper establishes a new pseudoisotopy result for embedding spaces, leading to computations of homotopy groups of long knots.

problem Computing homotopy groups of spaces of long knots in high codimension.
method Using pseudoisotopy results and algebraic K-theory, the paper describes the difference in homotopy types of block and ordinary embeddings of a codimension at least three embedding.
result The homotopy type of spaces of long knots of codimension at least 3 is determined explicitly, including torsion information.