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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.

168,742 papers · 148 categories

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48 results for topological interpretation

TopInG improves graph interpretability using persistent homology.

problem Lack of interpretability in Graph Neural Networks (GNNs).
method TopInG uses persistent homology to identify persistent rationale subgraphs in graphs.
result TopInG improves predictive accuracy and interpretability compared to state-of-the-art methods.

Study topological quantum mechanics on orbifolds with geometric interpretation.

problem Quantum mechanical models on symplectic orbifolds.
method Explicit orbifold version of quantum HKR map and exact semi-classical approximation.
result Geometric and quantum field theoretic interpretation of orbifold algebraic index.

GeoTop resolves topological ambiguity in diagnostic imaging using geometric-topological analysis.

problem Topological equivalence between benign and malignant structures in diagnostic images.
method Combines Topological Data Analysis and Lipschitz-Killing Curvatures to resolve ambiguity.
result Achieves 3.6% accuracy improvement and reduces false positives/negatives by 15-18%.

STS clarifies chaos and stochastic dynamics, linking algebraic topology and physics.

problem Chaos and stochastic dynamics in arbitrary form SDEs.
method Supersymmetric theory of stochastic dynamics (STS) using generalized transfer operator (GTO) and topological field theories (TFT).
result Positive 'pressure' in GTOs corresponds to spontaneous breakdown of topological supersymmetry, explaining 1/f noise.

Method quantifies disentanglement of generative models using manifold topology.

problem Challenging and inconsistent measurement of disentanglement in generative models.
method Measures topological similarity of conditional submanifolds in learned representation.
result Method ranks models similarly to existing methods across multiple datasets.

We introduce a notion of topological quandle. Given a topological quandle QQ we associate to every classical link LL in R3\R ^3 an invariant JQ(L)J_Q(L) which is a topological space (defined up to a homeomorphism). The space JQ(L)J_Q(L) can be interpreted as a space of colourings of a diagram of the link LL with colours f…

2005-08-26abs ↗pdf ↗

Topological method detects Hopf bifurcations from time series.

problem Detecting Hopf bifurcations in nonlinear systems from time series data.
method Persistent homology applied to Takens embedding for phase space reconstructions.
result A simple scalar topological functional identifies critical bifurcation points.

This paper introduces TDA and TSI for better business analytics.

problem Nonlinear, multi-scale business datasets under-represented by traditional tools.
method Topological Data Analysis (TDA) and Topological Stability Index (TSI).
result TSI reveals structural variability in business data.

This paper studies the canonical Chow quotient of a smooth projective variety by a reductive algebraic group. The main purpose is to give some topological interpretations and characterization of Chow quotient which have the advantage to be more intuitive and geometric. This is to be done over the field of complex numbe…

2003-08-04abs ↗pdf ↗

Method interprets deep learning models using topological data analysis.

problem Lack of interpretability in deep learning models, especially in high-risk applications.
method Topological and geometric data analysis to infer features and decision-making mechanisms of DL models.
result Extracted subgraphs reveal relevant features for model decisions, demonstrating model's reliance on pertinent data.

We make a precision test of a recently proposed conjecture relating Chern-Simons gauge theory to topological string theory on the resolution of the conifold. First, we develop a systematic procedure to extract string amplitudes from vacuum expectation values (vevs) of Wilson loops in Chern-Simons gauge theory, and then…

2000-04-27abs ↗pdf ↗

PHLP uses persistent homology to interpret graph link prediction.

problem Interpreting why graph neural network models perform well in link prediction.
method Employing persistent homology to analyze graph topology and extract features.
result PHLP outperforms state-of-the-art models on most benchmark datasets.

We study the algebraic and geometric properties of stated skein algebras of surfaces with punctured boundary. We prove that the skein algebra of the bigon is isomorphic to the quantum group Oq2(SL(2)){\mathcal O}_{q^2}(\mathrm{SL}(2)) providing a topological interpretation for its structure morphisms. We also show that its sta…

2019-07-26abs ↗pdf ↗

New compactification for character varieties with good topological properties.

problem Compactification of character varieties with good topological properties.
method Announced a new compactification with interpretations of ideal points.
result Relates to Weyl chamber length compactification and applies to maximal and Hitchin representations.

SOM-VQ tokenizes discrete models with semantic structure and navigable topology.

problem Lack of semantic structure in vector quantized representations limits interpretable human control.
method Combines vector quantization with Self-Organizing Maps to learn discrete codebooks with explicit topology.
result SOM-VQ produces more learnable token sequences and provides an explicit navigable geometry in code space.

We indicate how to combine some classical topology (Thom's work on the Steenrod problem) with some modern topology (simplicial volume) to show that every map between certain manifolds must have degree zero. We furthermore discuss a homotopy theoretic interpretation of parts of our proof, using Thom spaces and Steenrod …

2018-08-12abs ↗pdf ↗

Paper introduces a framework for diagnosing Alzheimer's disease using higher-order topological features from fMRI.

problem Diagnosing Alzheimer's disease using brain network topology.
method Persistent homology to extract higher-order features (cycles, cavities) from fMRI data.
result Framework significantly outperforms existing methods in AD classification.

We conjecture a relation between the sl(N) knot homology, recently introduced by Khovanov and Rozansky, and the spectrum of BPS states captured by open topological strings. This conjecture leads to new regularities among the sl(N) knot homology groups and suggests that they can be interpreted directly in topological st…

2004-12-20abs ↗pdf ↗

On the Geroch-Kronheimer-Penrose future completion IP(X)IP(X) of a spacetime XX, there are two frequently used topologies. We systematically examine τ+τ_+, the stronger (metrizable) of them, which is the coarsest causally continuous topology, obtaining a variety of novel results, among them a complete characterization of…

2019-09-09abs ↗pdf ↗

GISST interprets GNNs by combining attention and sparsity for graph structure and node feature importance.

problem Lack of joint consideration of graph structure and node features in GNN interpretation.
method Model-agnostic framework using attention mechanism and sparsity regularization.
result GISST achieves superior node feature and edge explanation precision in synthetic and real-world datasets.

A novel method extracts topological features from word embeddings for text classification.

problem High dimensional and noisy text representations in natural language processing.
method Persistent homology for topological data analysis on word embeddings.
result Topological features outperform conventional text mining features on long textual documents.

Paper introduces topological eigenvalue theorems for tensor analysis in multi-modal data.

problem Lack of deep understanding of tensor structures in multi-modal data fusion.
method Introduces topological perspective to tensor eigenvalue analysis, linking eigenvalues to topological features.
result Establishes new theorems that enhance understanding of tensor structures in data fusion.

Bayesian optimisation with graph kernels improves neural architecture search and provides interpretability.

problem Lack of insight into why architectures perform well and how to improve them.
method Combines Bayesian optimisation with Weisfeiler-Lehman graph kernels for highly data-efficient and interpretable architecture search.
result Demonstrates state-of-the-art performance on closed- and open-domain search spaces.

This paper is an exposition of the new subject of String Topology. We present an introduction to this exciting new area, as well as a survey of some of the latest developments, and our views about future directions of research. We begin with reviewing the seminal paper of Chas and Sullivan, which started String Topolog…

2005-03-28abs ↗pdf ↗

We implement methods from computational homology to obtain a topological signal of singularity formation in a selection of geometries evolved numerically by Ricci flow. Our approach, based on persistent homology, produces precise, quantitative measures describing the behavior of an entire collection of data across a di…

2015-02-09abs ↗pdf ↗

We give a topological interpretation of the space of L2L^2 harmonis forms of some QALE manifolds introduced by D. Joyce. We introduce a analytical criterium which make possible the used of Mayer-Vietoris sequence.

2005-01-19abs ↗pdf ↗

This paper provides a topological interpretation for number theoretic properties of quantum invariants of 3-manifolds. In particular, it is shown that the p-adic valuation of the quantum SO(3)-invariant of a 3-manifold M, for odd primes p, is bounded below by a linear function of the mod p first betti number of M. Shar…

1998-09-22abs ↗pdf ↗

Study topological G₂ and Spin(7) strings at 1-loop using double complexes.

problem Calculate topological string partition functions at 1-loop.
method Define double complexes for supersymmetric backgrounds using generalised geometry, compute partition functions as alternating products of determinants of Laplacians.
result Reproduce known results for G₂ string and predict for Spin(7) string.

Study of spectral invariants on CR contact manifolds with circle action.

problem Analytic torsion and eta-like invariants on CR contact manifolds.
method Interpret spectral series topologically and dynamically using Reeb flow.
result Spectral series can be interpreted both topologically and dynamically.

CAMEL enhances manifold embedding and learning with curvature metrics.

problem High-dimensional data classification, dimension reduction, and visualization.
method CAMEL uses a Riemannian manifold with curvature metrics for enhanced expressibility and interpretability.
result CAMEL outperforms state-of-the-art methods on high-dimensional datasets.

The paper generalizes Yang-Mills theory to study four-manifold topology.

problem Understanding the topology of diffeomorphism groups of four-manifolds.
method Path integral formulation of supersymmetric Yang-Mills coupled to conformal supergravity.
result The invariants may contain nontrivial information about the topology of the diffeomorphism group.

Study approximates top Lyapunov exponents for surface mapping classes.

problem Approximating topological Lyapunov exponents for surface mapping classes.
method Periodic approximation and joint spectral radius extension.
result Top Lyapunov exponents can be approximated by periodic orbits.

We introduce the concept of community trees that summarizes topological structures within a network. A community tree is a tree structure representing clique communities from the clique percolation method (CPM). The community tree also generates a persistent diagram. Community trees and persistent diagrams reveal topol…

2017-10-11abs ↗pdf ↗

We define and study spectral data associated to U(m,m)-Higgs bundles through the Hitchin fibration. We give a new interpretation of the topological invariants involved, as well as a geometric description of the moduli space.

2013-07-16abs ↗pdf ↗

We give a topological interpretation of the space of L2-harmonic forms on finite-volume manifolds with sufficiently pinched negative curvature. We give examples showing that this interpretation fails if the curvature is not sufficiently pinched and that our result is sharp with respect to the pinching constants. The me…

2002-07-12abs ↗pdf ↗

Survey on Allen-Cahn equations and systems, focusing on multiplicity results and geometric interpretation.

problem Multiplicity results for Allen-Cahn equations and systems in singular perturbation regime.
method Photography method, variational-topological approach based on localized approximate solutions and barycenter maps.
result Encoding of topology into multiplicity results through variational-topological approach.