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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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48 results for fine 1-curve graph

New findings on hyperbolicity of fine curve graphs and their subgraphs.

problem Investigating hyperbolicity of fine curve graphs and their subgraphs.
method Analyzing large subgraphs of fine curve graphs and computing distances in specific cases.
result Large subgraphs of fine curve graphs contain flats of every finite dimension, indicating they are not hyperbolic.

It is proved that the suspension of a closed n-dimensional manifold M, n1n\ge1, does not embed in a product of n+1 curves. In fact, the ultimate result will be proved in a much more general setting. This is a far-reaching generalization the Borsuk theorem on non-embeddability of the (n+1)-dimensional sphere in a produc…

2009-06-25abs ↗pdf ↗

The fine curve graph is hyperbolic and contains all countable graphs as induced subgraphs.

problem Characterizing the structure and properties of fine curve graphs.
method Analyzing the hyperbolicity and induced subgraph properties of fine curve graphs and their direct limits.
result The finitary curve graph has diameter 2, contains every countable graph as an induced subgraph, and has the homeomorphism group of the surface as its automorphism group.

Automorphisms of fine curve graphs match surface homeomorphisms for planar surfaces.

problem Understanding automorphisms of fine curve graphs on surfaces.
method Analyzing vertices and edges of fine curve graphs to match with surface homeomorphisms.
result Automorphism group of fine curve graphs is naturally isomorphic to the homeomorphism group of boundaryless planar surfaces with at least 7 punctures.

The paper studies the connectedness of a graph's boundary for surfaces.

problem Understanding the topology of the Gromov boundary of fine curve graphs for surfaces.
method Proved a bounded geodesic image theorem, used to show linear connectivity of the Gromov boundary.
result The Gromov boundary of fine curve graphs for surfaces is linearly connected.

Automorphism group of nonorientable surface curve graph matches surface homeomorphisms.

problem Identifying automorphisms of nonorientable surface curve graphs.
method Using Bowden, Hensel, and Webb's fine curve graph and Long, Margalit, Pham, Verberne, and Yao's proof as a foundation.
result Automorphism group of nonorientable surface curve graph is isomorphic to the surface's homeomorphism group.

Characterizes geometric actions on graphs with flexible stabilizers.

problem Understanding geometric actions on flexible stabilizers.
method Defining generalized fine actions and proving relative quasi-convexity criteria.
result Characterizes Bowditch boundary points in relatively geometric actions.

The study proves conditions for hyperbolic isometries on fine curve graphs of higher genus surfaces.

problem Conditions for hyperbolic isometries on fine curve graphs of higher genus surfaces.
method Proves equivalence of conditions involving isotopic maps, pseudo-Anosov maps, and ergodic rotation sets.
result Ergodic homological rotation sets have nonempty interior for certain isotopic maps.

Stable cylinders found in hyperbolic groups and curve graphs.

problem Torsionfree hyperbolic groups and curve graphs of surfaces have globally stable cylinders.
method Generalised Sageev's construction to improve fine properties of hyperbolic spaces.
result Proved curve graphs of surfaces admit equivariant quasi-isometric embeddings in finite products of quasitrees.

Abstract: Proves generic torus diffeomorphisms act parabolically and non-properly on fine curve graph and have generalized rotation sets.

problem Generic torus diffeomorphisms on fine curve graph.
method Proves generic torus diffeomorphisms act parabolically and non-properly on fine curve graph.
result Generic torus diffeomorphisms have generalized rotation sets of any point-symmetric compact convex homothety type.

Fine-tunes GNNs by preserving generative patterns to improve transferability.

problem Vanilla fine-tuning fails due to structural divergence between pre-training and downstream graphs.
method G-Tuning, which reconstructs the generative patterns of the downstream graph using graphon bases.
result G-Tuning achieves an average improvement of 0.5% and 2.6% on in-domain and out-of-domain transfer learning experiments.

New framework learns labels at both bag and graph levels.

problem Learning multi-label classifiers from multi-graph bags.
method Designing scoring functions and rank-loss objective for graph and bag levels; developing sub-gradient descent algorithm.
result Superior performance over state-of-the-art algorithms.

Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering. In this paper, we present Graph-Regularized Image Semantic Embedding (Graph-RISE), a large-scale neural graph learning framework that allows us to tr…

2019-02-14abs ↗pdf ↗

A new neural network model for molecular graphs that learns efficiently and accurately.

problem Learning on molecular graphs with cycles and complex structures.
method Hierarchical inter-message passing using raw graph and junction tree representations.
result The model outperforms classical GNNs in detecting cycles and is efficient to train.

Study homeomorphisms on fine curve graph of surfaces, revealing new types of dynamics.

problem Understanding dynamics of homeomorphisms on fine curve graphs of surfaces.
method Analyzing the action of homeomorphisms on the fine curve graph and relating to classical curve graphs.
result Homeomorphisms induce parabolic isometries, and all positive reals are realized as asymptotic translation lengths.

We prove that, given H<1|H|<1, a generic simple closed curve embedded in the asymptotic boundary of H3\mathbb{H}^3 (with respect to the supremum metric) bounds more than one complete surface embedded in H3\mathbb{H}^3 which has constant mean curvature HH. We remark that this is not true for the space of simple closed $…

2016-02-05abs ↗pdf ↗

The paper proposes DEA to make graph neural networks fairer in link prediction.

problem Graph neural networks can unfairly prioritize certain social groups in link prediction.
method Drop Edges and Adapt (DEA) fine-tuning strategy with covariance constraints.
result DEA improves fairness and accuracy in link prediction tasks.

PSimGNN partitions graphs into subgraphs for efficient graph similarity computation.

problem Efficiently compute graph similarity scores for large graphs.
method Graph partitioning followed by subgraph-level and node-level comparisons using a graph neural network.
result PSimGNN outperforms state-of-the-art methods in graph similarity computation tasks.

Study on stable translation lengths of surface homeomorphisms and their approximations.

problem Understanding stable translation lengths of homeomorphisms and their finite approximations.
method Comparing stable translation lengths of homeomorphisms and their finite approximations on curve graphs.
result Stable translation length of homeomorphisms with dense periodic points equals the supremum of their approximations.

The ropelength of a knot is the quotient of its length and its thickness, the radius of the largest embedded normal tube around the knot. We prove existence and regularity for ropelength minimizers in any knot or link type; these are C1,1C^{1,1} curves, but need not be smoother. We improve the lower bound for the ropelen…

2001-03-30abs ↗pdf ↗

We give the details of the proof of the equality between the critical groups, with respect the H^1 and C^1 topology, at a non-degenerate critical point of the energy functional of a non-reversible Finsler manifold (M,F), defined on the Hilbert manifold of the H^1 curves connecting two given points on M.

2012-11-13abs ↗pdf ↗

ADSAGE detects anomalies in graph edge sequences for insider threat detection.

problem Detecting insider threats in fine-grained audit logs using graph and text features.
method Anomaly detection at edge level, supporting numeric, categorical, and text attributes.
result ADSAGE detects anomalies in authentications and email communications effectively.

PanRep learns universal node embeddings for heterogeneous graphs.

problem Learning universal node embeddings for heterogeneous graphs.
method Graph Neural Network (GNN) model with four decoders capturing different properties.
result PanRep outperforms unsupervised and supervised methods in node classification and link prediction.

Heterogeneous GNN improves species distribution modeling.

problem Predicting species occurrences and habitat suitability using environmental factors.
method Graph Neural Networks (GNN) for presence-only species distribution modeling.
result Heterogeneous GNN model outperforms single-species SDMs and baseline models.

Any sequence of properly embedded minimal disks in an open subset U of Euclidean 3-space has a subsequence such that the curvatures blow up on a relatively closed subset K of U and such that the disks converge in the complement of K to a minimal lamination of U\K. Assuming results of Colding-Minicozzi and an extension …

2011-03-29abs ↗pdf ↗

Steinhaus conjectured that every closed oriented C1C^1-curve has a pair of anti-parallel tangents. Porter disproved the conjecture by showing that there exist curves with no anti-parallel tangents. Colin Adams rised the question of whether there exists a nontrivial knot in R3\R^3 which has no parallel or antiparallel t…

1999-12-06abs ↗pdf ↗

We construct Colding-Minicozzi limit minimal laminations in open domains in $\rth$ with the singular set of C1C^1-convergence being any properly embedded C1,1C^{1,1}-curve. By Meeks' C1,1C^{1,1}-regularity theorem, the singular set of convergence of a Colding-Minicozzi limit minimal lamination L{\cal L} is a locally finit…

2005-11-15abs ↗pdf ↗

We first study the degeneration of a sequence of Hermitian-Yang-Mills metrics with respect to a sequence of balanced metrics on a Calabi-Yau threefold X^\hat{X} that degenerates to the balanced metric constructed by Fu, Li, and Yau on the complement of finitely many (-1,-1)-curves in X^\hat{X}. Then under some assumpti…

2010-12-14abs ↗pdf ↗

SGQuant reduces GNN memory usage without significant accuracy loss.

problem High memory consumption in GNNs limits their applicability on memory-constrained devices.
method Proposes a specialized GNN quantization scheme (SGQuant) with a quantization algorithm, fine-tuning scheme, and multi-granularity strategy.
result SGQuant reduces GNN memory footprint from 4.25x to 31.9x with minimal accuracy loss.