arXiv research

The paper studies quaternionic structures on GKM graphs and their relation to torus actions on quaternionic projective spaces.

Investigates conditions for GKM fiber bundles and realizability of fiber bundles of GKM graphs.

Study GKM actions on special manifolds with interval orbit spaces.

The equivariant cohomology ring of a GKM manifold is isomorphic to the cohomology ring of its GKM graph. In this paper we explore the implications of this fact for equivariant fiber bundles for which the total space and the base space are both GKM and derive a graph theoretical version of the Leray-Hirsch theorem. Then…

The aim of this paper is to give an upper bound for the dimension of a torus $T$ which acts on a GKM manifold $M$ effectively. In order to do that, we introduce a free abelian group of finite rank, denoted by $\mathcal{A}(Γ,α,\nabla)$, from an (abstract) $(m,n)$-type GKM graph $(Γ,α,\nabla)$. Here, an $(m,n)$-type GKM …

We describe a generalization of GKM theory for actions of arbitrary compact connected Lie groups. To an action satisfying the non-abelian GKM conditions we attach a graph encoding the structure of the non-abelian 1-skeleton, i.e., the subspace of points with isotopy rank at most one less than the rank of the acting gro…

The paper classifies and constructs 6D GKM manifolds with 4 fixed points.

The study examines the independence of GKM manifolds and symmetric spaces.

Let T be a torus of dimension at least k and M a T-manifold. M is a GKM_k-manifold if the action is equivariantly formal, has only isolated fixed points, and any k weights of the isotropy representation in the fixed points are linearly independent. In this paper we compute the cohomology rings with real and integer coe…

Survey on GKM theory in low dimensions, highlighting combinatorics-geometry interplay.

Automorphisms of Hessenberg varieties are algebraic tori of dimension n-1.

We prove for closed, odd-dimensional GKM$_3$ manifolds of non-negative sectional curvature that both the equivariant and the ordinary rational cohomology split off the cohomology of an odd-dimensional sphere.

Let $G$ be a torus and $M$ a compact Hamiltonian $G$-manifold with finite fixed point set $M^G$. If $T$ is a circle subgroup of $G$ with $M^G=M^T$, the $T$-moment map is a Morse function. We will show that the associated Morse stratification of $M$ by unstable manifolds gives one a canonical basis of $K_G(M)$. A key in…

The one-skeleton of a G-manifold M is the set of points p in M where $\dim G_p \geq \dim G -1$; and M is a GKM manifold if the dimension of this one-skeleton is 2. Goresky, Kottwitz and MacPherson show that for such a manifold this one-skeleton has the structure of a ``labeled" graph, $(Γ, α)$, and that the equivariant…

In this paper we study non-negatively curved and rationally elliptic GKM$_4$ manifolds and orbifolds. We show that their rational cohomology rings are isomorphic to the rational cohomology of certain model orbifolds. These models are quotients of isometric actions of finite groups on non-negatively curved torus orbifol…

Let $Γ$ be a finite d-valent graph and G an n-dimensional torus. An ``action'' of G on $Γ$ is defined by a map, $α$, which assigns to each oriented edge e of $Γ$ a one-dimensional representation of G (or, alternatively, a weight, $α_e$, in the weight lattice of G). For the assignment, $e \to α_e$, to be a schematic des…

We investigate the equivariant cohomology of the natural torus action on a K-contact manifold and its relation to the topology of the Reeb flow. Using the contact moment map, we show that the equivariant cohomology of this action is Cohen-Macaulay, which is a generalization of equivariant formality for torus actions wi…

Study of CR-submanifolds in various Lorentzian manifolds.

Let $M$ be a symplectic manifold equipped with a Hamiltonian action of a torus $T$. Let $F$ denote the fixed point set of the $T$-action and let $i:F\hookrightarrow M$ denote the inclusion. By a theorem of F. Kirwan \cite{K} the induced map $i^*:H_T^*(M) \to H_T^*(F)$ in equivariant cohomology is an injection. We give …

The paper studies almost complex torus manifolds using graphs and Hirzebruch genera, proving properties of their fixed points and cohomology.

In 1998, Goresky, Kottwitz, and MacPherson showed that for certain spaces X equipped with a torus action, the T-equivariant cohomology ring of X can be described by combinatorial data obtained from its orbit decomposition. Thus, their theory transforms calculations of the equivariant topology of X to those of the combi…

Improved private learning for Littlestone classes with a doubly-exponential mistake bound.

Line graph transformation aids graph isomorphism tests by excluding challenging graph properties.

Proposes MGMN for end-to-end graph similarity learning.

The paper explores graphons of line graphs from sparse finite graphs.

MxPool learns graph features from diverse graphs using a hierarchical structure.

Study the geometry of graph product extension graphs.

Quasi-transitive graphs quasi-isometric to planar graphs can be upgraded to Cayley graphs.

Customized-GNN generates model-specific for each graph.

Graph embedding leaks sensitive graph properties and subgraphs.

Characterizes graphs with leveled embeddings and introduces new graph invariants.

The paper shows conflict graphs of Petersen family graphs are mostly unbalanced.

Two new methods improve graph embedding without needing a complete graph structure.

We define a pseudo-inverse for line graphs using linear integer programming.

Develops method to create non-Abelian Ricci-flat graphs via bundles.

New method uses graph generative models for graph classification.

MathNet uses wavelets for graph representation and learning.

Unified framework for graph coarsening using node features and graph matrices.

A fast graph embedding method for large graphs.

Quadratic bounds found for graph dimensions.

Study classifies Halin graphs with positive curvature.

PSimGNN partitions graphs into subgraphs for efficient graph similarity computation.

We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform can be obtained …

This paper develops graph theory for racks and quasigroups.

Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters in graph CNNs are built for fixed and shared graph structure. However, for most real data, the graph structures varies in both size and con…

We introduce a novel approach to graph-level representation learning, which is to embed an entire graph into a vector space where the embeddings of two graphs preserve their graph-graph proximity. Our approach, UGRAPHEMB, is a general framework that provides a novel means to performing graph-level embedding in a comple…

Graph Cascades rewire graphs to improve structure-aware learning.

CTGCN learns dynamic graph embeddings preserving both local and global graph structure.