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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.

168,695 papers · 148 categories

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54108161215 · May 202619922001200920172026
48 results for vertex leveling

In this paper, we develop a new aligned vertex convolutional network model to learn multi-scale local-level vertex features for graph classification. Our idea is to transform the graphs of arbitrary sizes into fixed-sized aligned vertex grid structures, and define a new vertex convolution operation by adopting a set of…

2019-02-26abs ↗pdf ↗

The L1 loss landscape of neural nets near local minima behaves differently, revealing exponential decay and increased vertex density.

problem Understanding the L1 loss landscape of neural nets near local minima.
method Iterative minimization of the loss function on adjacent vertices of the Deep ReLU Simplex algorithm.
result Exponential decay of loss levels and increased vertex density around local minima.

Investigates the vertex curve of smooth surfaces in 3D space, connecting geometry and image analysis.

problem Understanding the geometry of smooth surfaces in 3D space.
method Analyzes the vertex curve, related to differential geometry and symmetry sets of isophote curves.
result Establishes connections between the vertex curve and other geometric curves like parabolic and flecnodal curves.

Graph matching with feature vectors is solved using a two-layer graph neural network.

problem Graph matching in the presence of sparse binary features.
method Two-layer graph neural network with graph structure.
result Graph neural network can recover correct mapping with high probability under certain conditions.

Proposes methods to recover labels from shuffled networks using graph averages.

problem Recovering labels from a shuffled network using graph averages.
method Cluster networks into classes, then match the new graph to cluster-averages, minimizing the graph matching objective function.
result Higher fidelity matching performance when clustering networks into different classes.

A new hypergraph expansion method treats vertices and hyperedges equally, improving node classification.

problem Information loss in hypergraph expansions on either vertex or hyperedge level.
method Proposes a new hypergraph formulation named line expansion (LE) that treats vertices and hyperedges symmetrically.
result The proposed line expansion method outperforms state-of-the-art baselines on five hypergraph datasets.

New method embeds correlation networks to reveal underlying time series patterns.

problem Analyzing correlation networks derived from time series data.
method Spectral embedding of noisy correlation networks, leveraging Fourier basis elements.
result Spectral embedding recovers true vertex-level latent representations under suitable assumptions.

Given a vertex of interest in a network G1G_1, the vertex nomination problem seeks to find the corresponding vertex of interest (if it exists) in a second network G2G_2. A vertex nomination scheme produces a list of the vertices in G2G_2, ranked according to how likely they are judged to be the corresponding vertex of …

2017-11-15abs ↗pdf ↗

634 vertex-transitive and over 10^103 non-vertex-transitive 27-vertex triangulations of octonionic projective plane.

problem Constructing and classifying triangulations of the octonionic projective plane.
method Combinatorial construction and analysis of symmetry groups.
result Found 634 vertex-transitive and over 10^103 non-vertex-transitive 27-vertex triangulations.

Proposes a new method to describe graph vertex features using characteristic functions.

problem Describing the distribution of vertex features at multiple scales on graphs.
method Introduces FEATHER, a computationally efficient algorithm to calculate characteristic functions based on random walk transition probabilities.
result Demonstrates that the proposed method creates high-quality graph representations and is robust to data corruption.

Method analyzes large-scale network data to detect communication pattern shifts.

problem Analyzing large-scale time-series network data is challenging.
method Temporal encoder embedding method using ground-truth or estimated vertex labels.
result Detects communication pattern shifts across all levels of network structure.

Quasi-vertex-transitive maps are the homogeneous maps on the plane with finitely many vertex orbits under the action of their automorphism groups. We show that there exist quasi-vertex-transitive maps of types [p3,3][p^3, 3] for p1p \equiv 1 (mod 66), but there doesn't exist vertex-transitive map of such types. In particu…

2019-09-19abs ↗pdf ↗

For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by appropriate vertex classification is asymptotically Bayes optimal; but this approach requires knowledge of and critically depends on the model dimension. In this paper, w…

2013-11-23abs ↗pdf ↗

New proof for global rigidity of vertex scaling on polyhedral surfaces.

problem Global rigidity of vertex scaling on polyhedral surfaces.
method Elementary variational proof based on continuity of eigenvalues and extension of convex functions.
result Global rigidity of vertex scaling proved without involving 3D hyperbolic geometry.

A semi-regular tiling of the hyperbolic plane is a tessellation by regular geodesic polygons with the property that each vertex has the same vertex-type, which is a cyclic tuple of integers that determine the number of sides of the polygons surrounding the vertex. We determine combinatorial criteria for the existence, …

2018-06-29abs ↗pdf ↗

Given a graph in which a few vertices are deemed interesting a priori, the vertex nomination task is to order the remaining vertices into a nomination list such that there is a concentration of interesting vertices at the top of the list. Previous work has yielded several approaches to this problem, with theoretical re…

2016-07-05abs ↗pdf ↗

The paper explores how to find relevant vertices in one graph using another graph's attributes and structure.

problem Finding relevant vertices in one graph using another graph's attributes and structure.
method Theoretical and practical exploration of vertex nomination schemes that leverage both content (edge and vertex attributes) and context (network topology).
result Necessary and sufficient conditions for schemes that use both content and context to outperform those using only one.

Let MM be a Riemannian manifold. For pMp\in M, the tensor algebra of the negative part of the (complex) affinization of the tangent space of MM at pp has a natural structure of a meromorphic open-string vertex algebra. These meromorphic open-string vertex algebras form a vector bundle over MM with a connection. We …

2012-05-14abs ↗pdf ↗

Marked vertex diagrams provide a combinatorial way to represent knotted surfaces in R4\mathbb{R}^4; including virtual crossings allows for a theory of virtual knotted surfaces and virtual cobordisms. Biquandle counting invariants are defined only for marked vertex diagrams representing knotted orientable surfaces; we e…

2014-09-27abs ↗pdf ↗

Consider a group G and a family A\mathcal{A} of subgroups of G. We say that vertex finiteness holds for splittings of G over A\mathcal{A} if, up to isomorphism, there are only finitely many possibilities for vertex stabilizers of minimal G-trees with edge stabilizers in A\mathcal{A}. We show vertex finiteness when G…

2013-11-12abs ↗pdf ↗

Researchers link vertex algebras to non-Kähler solutions of the Hull-Strominger system.

problem Constructing representations of vertex algebras from non-Kähler solutions of the Hull-Strominger system.
method Embedding the N=2 superconformal vertex algebra in the chiral de Rham complex of a string Courant algebroid, with a condition on the Hermitian-Yang-Mills connection.
result Any solution of the Hull-Strominger system satisfying the Hermitian-Yang-Mills condition has an associated N=2 embedding.

Given a finite graph of relatively hyperbolic groups with its fundamental group relatively hyperbolic and edge groups quasi-isometrically embedded and relatively quasiconvex in vertex groups, we prove that vertex groups are relatively quasiconvex if and only if all the vertex groups have finite relative height in the f…

2015-08-21abs ↗pdf ↗

Let G and F be finitely generated groups with infinitely many ends and let A and B be graph of groups decompositions of F and G such that all edge groups are finite and all vertex groups have at most one end. We show that G and F are quasi-isometric if and only if every one-ended vertex group of A is quasi-isometric to…

2004-05-14abs ↗pdf ↗

The study proves unique harmonic functions and combinatorial properties of vertex-transitive graphs.

problem Proving combinatorial properties of vertex-transitive graphs.
method Using harmonic functions and quasi-isometry to R\mathbb{R}, proving uniqueness and combinatorial results.
result Connective constant of non-degenerate vertex-transitive graphs is at least the golden mean.

The existence of a balanced vertex is proven for geodesic nets with three boundary vertices.

problem Existence of a balanced vertex in geodesic nets with specific boundary conditions.
method Proof of existence on a general two-dimensional Riemannian surface.
result Existence of a balanced vertex for geodesic nets with three unbalanced boundary vertices.

While many multiple graph inference methodologies operate under the implicit assumption that an explicit vertex correspondence is known across the vertex sets of the graphs, in practice these correspondences may only be partially or errorfully known. Herein, we provide an information theoretic foundation for understand…

2016-05-08abs ↗pdf ↗

Two spectral algorithms for community detection in graphs with covariates are compared.

problem Detecting community structure in graphs with covariates.
method Two model-based spectral algorithms are presented and compared.
result The second algorithm often better estimates block assignments by accounting for vertex covariates.