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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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96193289385 · May 202619922001200920172026
48 results for equivariant local principle

Derives Fredholm criteria for isotypical components from a Simonenko principle.

problem Finding Fredholm conditions for isotypical components of invariant pseudodifferential operators.
method General Simonenko's local principle and equivariant local principle for restriction to isotypical components.
result Full proof of equivariant local principle and extension of results.

Local-to-global principle for Morse actions on symmetric spaces.

problem Recognizing Morse actions on symmetric spaces.
method Equivariant Morse quasiisometric embeddings of trees into symmetric spaces.
result Algorithmic recognizability of Morse actions and construction of Morse Schottky subgroups.

The principle of equivariance to symmetry transformations enables a theoretically grounded approach to neural network architecture design. Equivariant networks have shown excellent performance and data efficiency on vision and medical imaging problems that exhibit symmetries. Here we show how this principle can be exte…

2019-02-11abs ↗pdf ↗

This paper introduces equivariant hamiltonian flows, a method for learning expressive densities that are invariant with respect to a known Lie-algebra of local symmetry transformations while providing an equivariant representation of the data. We provide proof of principle demonstrations of how such flows can be learnt…

2019-09-30abs ↗pdf ↗

The study examines how weight sharing, equivariance, and locality affect the sample complexity of neural networks.

problem Understanding the impact of design choices on the generalization error of neural networks.
method Statistical learning theory applied to single hidden layer networks with weight sharing, equivariance, and locality.
result Lower and upper bounds for sample complexity are derived, showing that locality has benefits but comes with a trade-off.

DNFS trains efficient samplers for discrete distributions using locally equivariant Transformers.

problem Sampling from unnormalised discrete distributions.
method DNFS learns a rate matrix to satisfy the Kolmogorov equation, using control variates and locally equivariant Transformers.
result DNFS achieves efficient and effective sampling across various applications.

In a strengthening of the G-Signature Theorem of Atiyah and Singer, we compute, at least in principle (modulo certain torsion of exponent dividing a power of the order of G), the class in equivariant K-homology of the signature operator on a G-manifold, localized at a prime idea of R(G), in terms of the classes in non-…

1998-12-22abs ↗pdf ↗

Unified classification of equivariant principal bundles using higher homotopy theory.

problem Unified classification of equivariant principal bundles.
method Smooth Oka principle, singular-cohesive homotopy theory, internally describing principal bundles.
result Unified classification results for equivariant principal bundles.

New graph foundation models respect symmetries for broader applicability.

problem Tailored graph machine learning architectures limit broader applicability.
method Investigates symmetries for label and feature permutations, proving network universal approximator.
result Universal approximator on multisets respecting node and feature permutations.

We propose and study the following Mirror Principle: certain sequences of multiplicative equivariant characteristic classes on Kontsevich's stable map moduli spaces can be computed in terms of certain hypergeometric type classes. As applications, we compute the equivariant Euler classes of obstruction bundles induced b…

1997-12-11abs ↗pdf ↗

In this paper, we provide a concrete interpretation of equivariant Reidemeister torsion and demonstrate that Bismut-Zhang's equivariant Cheeger-Müller theorem simplifies considerably when applied to locally symmetric spaces. In a companion paper, this allows us to extend recent results on torsion cohomology growth and …

2013-12-09abs ↗pdf ↗

We propose a new model for digital pathology segmentation, based on the observation that histopathology images are inherently symmetric under rotation and reflection. Utilizing recent findings on rotation equivariant CNNs, the proposed model leverages these symmetries in a principled manner. We present a visual analysi…

2018-06-08abs ↗pdf ↗

The Witten class is derived from equivariant cohomology of a conformal loop space.

problem Deriving the Witten class using equivariant cohomology.
method Applying equivariant localization formula to a conformal loop space.
result The Witten class is obtained from the conformal loop space.

A strong from of invariance under a group G is manifested in a family over the classifying space BG. We advocate a differential-geometric avatar of BG when G is a Lie group. Applied to G-equivariant connections on smooth principal or vector bundles, the equivariance-->families principle converts the G-equivariant exten…

2016-06-03abs ↗pdf ↗

We prove a localization formula for group-valued equivariant de Rham cohomology of a compact G-manifold. This formula is a non-trivial generalization of the localization formula of Berline-Vergne and Atiyah-Bott for the usual equivariant de Rham cohomology. As an application, we obtain a version of the Duistermaat-Heck…

1999-05-20abs ↗pdf ↗

The paper explores how equivariant models' biases affect latent representations for better performance.

problem The impact of inductive biases on latent representations in equivariant models.
method Demonstrates the importance of accounting for inductive biases in latent representations of equivariant models.
result Effective invariant projections can be used to retain information in latent representations, improving downstream tasks.

Proposes SE(3) equivariant graph neural networks with local frames for efficient geometric approximation.

problem Equivariance in deep learning for arbitrary transformations, especially in physics.
method Introduces SE(3) equivariant graph neural networks with complete local frames to efficiently approximate geometric quantities.
result Achieves best or competitive performance in Newton mechanics modeling and equilibrium molecule conformation generation.

New theory explains how equivariant self-supervised learning improves feature extraction.

problem Contrastive learning sacrifices useful features due to invariance to data augmentations.
method Information-theoretic perspective to understand E-SSL's generalization ability.
result Equivariant self-supervised learning creates synergy between equivariant and classification tasks.

New model preserves symmetry in multivariate time series, improving performance.

problem Implicit ordering in MTS models violates inherent exchangeability.
method Permutation-equivariant 2D state space model with canonical architecture.
result Eliminates sequential dependency chains and simplifies stability analysis.

LEAPS samples discrete distributions via CTMCs and locally equivariant networks.

problem Sampling from discrete distributions with known normalization.
method Continuous-time Markov chain, locally equivariant functions, attention layers, convolutional networks.
result LEAPS minimizes the variance of importance weights, improving sampling efficiency.

We give two generalizations of the Atiyah-Bott-Berline-Vergne localization theorem for the equivariant cohomology of a torus action: 1) replacing the torus action by a compact connected Lie group action, 2) replacing the manifold having a torus action by an equivariant map. This provides a systematic method for calcula…

2003-09-04abs ↗pdf ↗

In this paper, we first define the equivariant infinitesimal ηη-form, then we compare it with the equivariant ηη-form, modulo exact forms, by a locally computable form. As a consequence, we obtain the singular behavior of the equivariant ηη-form, modulo exact forms, as a function on the acting Lie group. This result…

2018-08-13abs ↗pdf ↗

LLoCa makes any network Lorentz-equivariant, achieving high accuracy and efficiency.

problem Limitations of specialized layers in Lorentz-equivariant neural networks.
method LLoCa framework using local reference frames and geometric message passing.
result Models achieve competitive and state-of-the-art accuracy on particle physics tasks.

In this paper, we prove equivariant Morse inequalities via Bismut-Lebeau's analytic localization techniques. As an application, we obtain Morse inequalities on compact manifold with nonempty boundary by applying equivariant Morse inequalities to the doubling manifold.

2012-05-15abs ↗pdf ↗

New rigidity results for complex and quaternionic moment-angle manifolds.

problem Equivariant topological rigidity of complex and quaternionic moment-angle manifolds.
method Reduction to equivariant rigidity of quasitoric (or quoric) quotients and principal bundles.
result Full equivariant rigidity for manifolds with four-dimensional quoric quotients and primary rigidity for higher dimensions.

Let G be a compact Lie group. Let M be a smooth G-manifold and V --> M be an oriented G-equivariant vector bundle. One defines the spaces of equivariant forms with generalized coefficients on V and M. An equivariant Thom form θθ on V is a compactly supported closed equivariant form such that its integral along the fib…

2004-02-04abs ↗pdf ↗

Consider a proper, isometric action by a unimodular, locally compact group GG on a complete Riemannian manifold MM. For equivariant elliptic operators that are invertible outside a cocompact subset of MM, we show that a localised index in the KK-theory of the maximal group CC^*-algebra of GG is well-defined. The …

2019-09-25abs ↗pdf ↗

A 2-torus manifold is a closed smooth manifold of dimension nn with an effective action of a 2-torus group (Z2)n(\Z_2)^n of rank nn, and it is said to be locally standard if it is locally isomorphic to a faithful representation of (Z2)n(\Z_2)^n on Rn\R^n. This paper studies the equivariant classification of locally standar…

2008-02-16abs ↗pdf ↗