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.
Proves spacetime positive mass theorem with corners.
Unified framework for Riemannian deep learning across manifold-valued representations.
Sharp constants in curl-Sobolev inequalities on spheres determined.
Develops relative harmonic metrics and deformation theory for Higgs and flat bundles on compact Kähler manifolds.
Develops a unified theory of Yang-Mills and GR using generalized principal bundles.
Paper proves existence of isometric immersions for negatively curved surfaces with unbounded second fundamental form.
The paper proves new inequalities on the unit ball in higher dimensions.
The paper explores spaces of Kähler and symplectic forms on 4-manifolds.
This paper classifies ball quotients of the complex projective plane.
Classifies degenerations of complex projective plane with rational singularities.
The paper explores the geometry and dynamics of free splitting and free factor complexes for groups.
Proves a mod 4 version of Kawauchi's conjecture for amphicheiral knots.
New findings show infinitely many non-homeomorphic manifolds with same proper homotopy type.
Khovanov homology fails to differentiate certain slice disks.
Study detects a specific type of link using annular Khovanov homology.
The paper characterizes simple closed curves on surfaces using profinite rigidity.
The pants graph of a non-orientable surface is quasi-isometric to its Teichmüller space.
New property helps show many knot fillings are not left-orderable.
A new method combines simple binary classifiers to build complex multiclass classifiers, achieving performance limits in a Gaussian setting.
A new algorithm improves posterior sampling for linear inverse problems.
Bayesian methods often misinterpret data and asymptotic concepts.
New PINNs method improves accuracy in computing Mean Escape Time from bounded domains.
Study compares different scoring rules for machine-learned weather forecasts, finding scale-awareness improves forecast realism.
Deep learning predicts adhesive forces in soft viscoelastic contacts quickly and accurately.
New characterization limits sampling with inexact scores.
The paper optimizes regret using covariance between costs and decisions.
Paper uses algebraic signatures to identify probabilistic structures in empirical data.
Quantum GBS boosts asset clustering for robust statistical arbitrage portfolios.
DSPM models control noise volatility, improving financial data analysis.
The paper models Gasoil options using Brent benchmarks, improving volatility estimation.
OMD monitors stock market dynamics through matrix trajectories, revealing crisis patterns and sector rotations.
Paper models cloud outages for cyber insurance stress-testing.
The study compares parametric and nonparametric models for estimating mean-variance mixtures and finds that nonparametric models perform better.
Develops portfolio theory without probabilistic analysis, focusing on pathwise decomposition.
Firms miscount their customers who stop buying without saying goodbye.
TabNet improves fraud detection in bank transactions.