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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.

169,051 papers · 148 categories

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48 results for co-index of symmetry

We develop a general structure theory for compact homogeneous Riemannian manifolds in relation to the co-index of symmetry. We will then use these results to classify irreducible, simply connected, compact homogeneous Riemannian manifolds whose co-index of symmetry is less or equal than three. We will also construct ma…

2013-12-20abs ↗pdf ↗

Study on Hitchin index for cohomogeneity one nearly Kähler structures.

problem Characterizing Hitchin index for cohomogeneity one nearly Kähler structures.
method Variational characterization, Morse-like index, cohomogeneity one symmetry, ODE eigenvalue problem.
result Obtained non-trivial lower bounds on Hitchin index for specific structure.

Let f be a smooth Morse function on an infinite dimensional separable Hilbert manifold, all of whose critical points have infinite Morse index and co-index. For any critical point x choose an integer a(x) arbitrarily. Then there exists a Riemannian structure on M such that the corresponding gradient flow of f has the f…

2004-03-31abs ↗pdf ↗

Investigates nearly Kähler and parallel G2 manifolds using Hitchin functionals.

problem Stability analysis of nearly Kähler and parallel G2 manifolds.
method Gradient flow of Hitchin functionals, spectral decomposition of Hessians, Hitchin index.
result Hitchin index provides a lower bound for the Einstein co-index.

Develops Bialynicki-Birula and Morse-Bott theory for complex analytic spaces.

problem Extending classical theories to complex analytic spaces with holomorphic C\mathbb{C}^* actions.
method Extends Bialynicki-Birula and Morse-Bott theories to non-compact complex manifolds and analytic spaces, proving existence and deriving geometric consequences.
result Existence of Bialynicki-Birula decompositions for C\mathbb{C}^*-invariant subspaces in complex manifolds.

The paper analyzes symmetries of Vaidya-Bonner geodesics.

problem Investigating invariance properties of Vaidya-Bonner geodesics.
method Classification of Lie point symmetries and Noether symmetries, determination of optimal system of subalgebras.
result Determination of optimal system of subalgebras for Vaidya-Bonner geodesics.

Method improves deep learning models for datasets with mixed approximate symmetries.

problem Improving deep learning models for datasets with mixed approximate symmetries.
method Regularizer-based approach to build models for datasets with mixed approximate symmetries.
result Our method achieves better accuracy than prior approaches while discovering the approximate symmetry levels correctly.

Symmetry in loss functions constrains model parameters, leading to specific learning outcomes.

problem Understanding and leveraging symmetries in neural networks to improve learning outcomes.
method Analyzing the impact of loss function symmetries on model parameters and learning behavior.
result Mirror-reflection symmetries in loss functions lead to constraints on model parameters, influencing learning outcomes.

Approximate symmetries of geodesic equations on 2-spheres are studied. These are the symmetries of the perturbed geodesic equations which represent approximate path of a particle rather than exact path. After giving the exact symmetries of the geodesic equations, two different approaches to study the approximate symmet…

2010-05-09abs ↗pdf ↗

New framework discovers non-affine continuous symmetries in neural networks.

problem Lack of efficient methods for detecting non-affine continuous symmetries in neural networks.
method Computational framework for discovering infinitesimal generators of multi-parameter group actions.
result Framework can discover non-affine continuous symmetries in neural networks.

Symmetry in neural networks reduces parameter count without sacrificing accuracy.

problem Improving parameter usage and efficiency in deep neural networks.
method Imposing symmetry constraints on neural network parameters, especially in convolutional and recurrent networks.
result Symmetry can have little or no negative effect on network accuracy, even in deep overparameterized networks.

This paper introduces a new approach to finding knots and links with hidden symmetries using "hidden extensions", a class of hidden symmetries defined here. We exhibit a family of tangle complements in the ball whose boundaries have symmetries with hidden extensions, then we further extend these to hidden symmetries of…

2015-01-04abs ↗pdf ↗

Symmetry of neural network densities can be determined from correlation functions.

problem Determining symmetries of neural network densities without knowing the density itself.
method Symmetry-via-duality approach using invariance properties of correlation functions.
result Symmetries of neural network densities can be determined via dual computations of correlation functions.

Clarifies relation between Pfaffian fibrations and relative algebroids.

problem Understanding geometric structures and symmetries in PDEs.
method Introduces and analyzes Pfaffian fibrations and relative algebroids, clarifying their relationship.
result Every Pfaffian fibration induces a relative algebroid, and their prolongations and local solutions coincide.

Noether's theorem clarifies how symmetries in neural networks influence learning.

problem Understanding how symmetries in neural networks affect learning.
method Systematic study of symmetry interactions with learning algorithms using Noether's theorem.
result Symmetries impose restrictions on the optimization path, leading to conserved quantities.

This work relaxes GNN symmetries to approximate automorphisms, improving model performance.

problem Improving graph neural network performance on asymmetric graphs.
method Formalizing approximate symmetries via graph coarsening, introducing a bias-variance formula.
result Best generalization performance achieved by choosing a larger symmetry group than automorphisms but smaller than permutations.

This paper aims to incorporate passive symmetries in machine learning for better generalization.

problem Machine learning's reliance on arbitrary choices leads to passive symmetries that can limit generalization.
method Translation among physics, mathematics, and machine learning to understand and implement passive symmetries.
result Respecting passive symmetries can improve machine learning's ability to generalize.

SymPE breaks symmetries in equivariant networks, improving performance across various tasks.

problem Equivariant networks cannot break symmetries, leading to poor performance in tasks with symmetrical inputs.
method Novel equivariant conditional distributions and randomized canonicalization.
result SymPE significantly improves performance of group-equivariant and graph neural networks.

Study of symmetries in 2D Yang-Mills theory, including orbifolds and higher forms.

problem Understanding symmetries and anomalies in 2D Yang-Mills theory.
method Combining continuum methods, topological defects, and higher gauge theory.
result Unified description of higher and lower form gauge fields, identifying spontaneous symmetry breaking.

Symmetries of Einstein-Weyl manifolds can be extended from boundary surfaces.

problem Extending symmetries from boundary surfaces to Einstein-Weyl manifolds.
method Starting from a symmetry of conformal Cartan connection on a boundary surface, proving symmetries can be extended.
result Symmetries of conformal Cartan connection on the boundary can be extended to symmetries of the Einstein-Weyl manifold.

We classify hyperbolic monopoles with continuous symmetries and construct new examples.

problem Classifying and constructing hyperbolic monopoles with continuous symmetries.
method Developed a Structure Theorem and used representation theory to simplify the problem.
result Found constraints on structure groups and constructed novel spherically symmetric Sp(n)\mathrm{Sp}(n) hyperbolic monopoles.

Symmetry-breaking in three differential geometry conjectures.

problem Exploring the role of symmetry in three differential geometry conjectures.
method Examining the Carathéodory, Willmore, and Lawson Conjectures through the lens of symmetry in 3D space-forms.
result Symmetry is broken, and more general ambient metrics are considered, leading to the failure of the conjectures.

Metric evaluates symmetry-breaking in datasets, revealing severe biases.

problem Symmetry-breaking in datasets can hinder the performance of symmetry-aware methods.
method Developed a metric to quantify symmetry-breaking using a two-sample classifier test.
result Symmetry-breaking can prevent optimal performance of invariant methods, even when labels are invariant.

Lie symmetry group method is applied to study the Born-Infeld equation. The symmetry group and its optimal system are given, and group invariant solutions associated to the symmetries are obtained. Finally the structure of the Lie algebra symmetries is determined.

2010-09-28abs ↗pdf ↗

Researchers develop Orlov-Schulman symmetries for self-dual conformal structures.

problem Developing symmetries for self-dual conformal structures.
method Explicit proof of compatibility with Lax-Sato flows, dressing scheme based on Riemann-Hilbert problem.
result Construction and proof of compatibility of Orlov-Schulman symmetries.

Symmetry improves machine learning models by reducing overfitting and complexity.

problem Ignoring symmetry in machine learning models can lead to overfitting and increased complexity.
method Incorporating symmetry into machine learning models, specifically neural networks for classifying handwritten digits.
result Incorporating symmetry into machine learning models reduces overfitting and complexity, requiring less training data and less time to train.

New triangulations of quaternionic projective plane found with various symmetry groups.

problem Classifying triangulations of quaternionic projective plane with 15 vertices.
method Constructing and classifying 15-vertex triangulations with various symmetry groups.
result Exactly 75 triangulations of quaternionic projective plane with 15 vertices and symmetry group of order at least 4.