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.
Signed seminorms linked to real tropical spaces and matroids.
We associate to any Riemannian symmetric space (of finite or infinite dimension) a L-algebra, under the assumption that the curvature operator has a fixed sign. L-algebras are Lie algebras with a pleasant Hilbert space structure. The L-algebra that we construct is a complete local isomorphism invariant and …
The article extends Thurston's Grafting Theorem to signed spaces and defines a framed monodromy map.
Study on blow-up behavior of sign-changing solutions for Yamabe equation.
SLIM model predicts social network polarization using signed links.
Study examines Kähler immersions of ALE Kähler metrics into complex space forms.
We give a characterization of alternating link exteriors in terms of cubed complexes. To this end, we introduce the concept of a "signed BW cubed-complex", and give a characterization for a signed BW cubed-complex to have the underlying space which is homeomorphic to an alternating link exterior.
The paper defines grid homologies for singular links in lens spaces and constructs a resolution cube for knot Floer homology.
A new algorithm solves signed Fréchet regression on manifolds with bounded curvature.
Study on signed graphs with random signs, focusing on community detection.
SELO model predicts link signs better than SDGNN using subgraph encoding and linear optimization.
New tests for high-dimensional data improve on existing methods.
We argue that the standard graph Laplacian is preferable for spectral partitioning of signed graphs compared to the signed Laplacian. Simple examples demonstrate that partitioning based on signs of components of the leading eigenvectors of the signed Laplacian may be meaningless, in contrast to partitioning based on th…
Novel GNN for signed and directed networks using magnetic signed Laplacian.
Sign equivariant networks improve model expressiveness for spectral geometric learning.
Defines signed quasiregular curves and proves growth theorem.
A Hilbert space embedding for probability measures has recently been proposed, wherein any probability measure is represented as a mean element in a reproducing kernel Hilbert space (RKHS). Such an embedding has found applications in homogeneity testing, independence testing, dimensionality reduction, etc., with the re…
Signed networks contain both positive and negative kinds of interactions like friendship and enmity. The task of node classification in non-signed graphs has proven to be beneficial in many real world applications, yet extensions to signed networks remain largely unexplored. In this paper we introduce the first analysi…
The study investigates deformations of swallowtails in 3D space, preserving curvature signs.
In this short note, we compare the combinatorial sign assignment of Manolescu, Ozsvath, Szabo and Thurston for grid homology of knots and links in 3-sphere with the sign assignment coming from a coherent system of orientations on Whitney disks. Although these constructions produce different signs, a small modification …
PyTorch Geometric Signed Directed fills the gap for GNNs on signed and directed graphs.
Proposes a privacy-preserving sign selection method for distributed systems.
In this article we introduce a diffeomorphism-invariant Riemannian metric on the space of vector valued one-forms. The particular choice of metric is motivated by potential future applications in the field of functional data and shape analysis and by connections to the Ebin metric on the space of all Riemannian metrics…
Paper introduces stable vectorization for multiparameter PH using signed barcodes.
Estimates graph curvature and diameter using Laplacian eigenvalues.
In this paper, we obtain nonexistence results of positive solutions, and also the existence of an unbounded sequence of solutions that changing sign for some critical problems involving conformally invariant operators on the standard unit sphere, and the fractional Laplacian operator in the Euclidean space. Our argumen…
The paper discovers patterns in Maass forms' coefficients related to Fricke signs.
Novel CNN array for sign language recognition using wearable IMUs.
The recognition of sign language is a challenging task with an important role in society to facilitate the communication of deaf persons. We propose a new approach of Spatial-Temporal Graph Convolutional Network to sign language recognition based on the human skeletal movements. The method uses graphs to capture the si…
In this paper we use theory of embedded graphs on oriented and compact -surfaces to construct minimal realizations of signed Gauss paragraphs. We prove that the genus of the ambient surface of these minimal realizations can be seen as a function of the maximum number of Carter's circles. For the case of signed Gaus…
CSNE embeds signed networks by separating structural and fine-grained information.
We use Reidemeister torsion to study a twisted Alexander polynomial, as defined by Turaev, for links in the projective space. Using sign-refined torsion we derive a skein relation for a normalized form of this polynomial.
The paper finds sign-changing solutions for a specific type of elliptic equation.
Unified sign-based compression for federated learning with faster convergence.
Signed graphs encode positive (attractive) and negative (repulsive) relations between nodes. We extend spectral clustering to signed graphs via the one-parameter family of Signed Power Mean Laplacians, defined as the matrix power mean of normalized standard and signless Laplacians of positive and negative edges. We pro…
Signed-permutation coordinate transport improves model alignment across checkpoints.
New method estimates tensors from noisy data with missing entries.
Signed heights of knotoids are defined and studied.
Develops method for learning signed graphs from smooth signals.
A new method learns node embeddings for signed directed networks by capturing both first-order and high-order topologies.
It is well-known that the Jones polynomial of an alternating knot is closely related to the Tutte polynomial of a special graph obtained from a regular projection of the knot. Relying on the results of Bollobás and Riordan, we introduce a generalization of Kauffman's Tutte polynomial of signed graphs for which describi…
In this paper, we recover sparse signals from their noisy linear measurements by solving nonlinear differential inclusions, which is based on the notion of inverse scale space (ISS) developed in applied mathematics. Our goal here is to bring this idea to address a challenging problem in statistics, \emph{i.e.} finding …
We present a method for learning the parameters of a Bayesian network with prior knowledge about the signs of influences between variables. Our method accommodates not just the standard signs, but provides for context-specific signs as well. We show how the various signs translate into order constraints on the network …
Traffic sign recognition is an important component of many advanced driving assistance systems, and it is required for full autonomous driving. Computational performance is usually the bottleneck in using large scale neural networks for this purpose. SqueezeNet is a good candidate for efficient image classification of …
In this paper we classify complete surfaces of constant mean curvature whose Gaussian curvature does not change sign in a simply connected homogeneous manifold with a 4-dimensional isometry group.
We analyse the problem of assigning sign choices to O-planes in orientifolds of type II string theory. We show that there exists a sequence of invariant -gerbes with , which give rise to sign choices and are related by coboundary maps. We prove that the sign choice homomorphisms stabilise with the dimension…
Derives curvature conditions for spatial isotropy without field equations.
New nodal domain theorems for symmetric matrices via signed graphs.