English
Related papers

Related papers: Equivariant Nerve Lemma, simplicial difference, an…

200 papers

Riemannian submanifold optimization with momentum is computationally challenging because, to ensure that the iterates remain on the submanifold, we often need to solve difficult differential equations. Here, we simplify such difficulties…

Machine Learning · Statistics 2024-03-19 Wu Lin , Valentin Duruisseaux , Melvin Leok , Frank Nielsen , Mohammad Emtiyaz Khan , Mark Schmidt

We present an alternative way of solving the steerable kernel constraint that appears in the design of steerable equivariant convolutional neural networks. We find explicit real and complex bases which are ready to use, for different…

Machine Learning · Computer Science 2026-03-16 Alan Garbarz

An action of a complex reductive group $\mathrm G$ on a smooth projective variety $X$ is regular when all regular unipotent elements in $\mathrm G$ act with finitely many fixed points. Then the complex $\mathrm G$-equivariant cohomology…

Algebraic Geometry · Mathematics 2026-05-27 Tamás Hausel , Kamil Rychlewicz

The treatment of the principle of general covariance based on coordinate systems, i.e., on classical tensor analysis suffers from an ambiguity. A more preferable formulation of the principle is based on modern differential geometry: the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Vladimir S. Mashkevich

Thomason's Homotopy Colimit Theorem has been extended to bicategories and this extension can be adapted, through the delooping principle, to a corresponding theorem for diagrams of monoidal categories. In this version, we show that the…

Category Theory · Mathematics 2011-03-24 A. R. Garzón , R. Pérez

Traditional supervised learning aims to learn an unknown mapping by fitting a function to a set of input-output pairs with a fixed dimension. The fitted function is then defined on inputs of the same dimension. However, in many settings,…

Machine Learning · Computer Science 2024-05-01 Eitan Levin , Mateo Díaz

We show that the classification diagram of a relative $\infty$-category arising from a relative simplicial category is equivalent to the levelwise nerve. Applications include the comparison of the diagonal of the levelwise nerve and the…

Algebraic Topology · Mathematics 2025-10-22 Kensuke Arakawa

The homotopy coherent nerve from simplicial categories to simplicial sets and its left adjoint C are important to the study of (infinity,1)-categories because they provide a means for comparing two models of their respective homotopy…

Category Theory · Mathematics 2011-04-01 Emily Riehl

We establish a purely geometric form of the concentration theorem (also called localization theorem) for actions of a linearly reductive group $G$ on an affine scheme $X$ over an affine base scheme $S$. It asserts the existence of a…

Algebraic Geometry · Mathematics 2025-03-27 Olivier Haution

We present a new approach to simple homotopy theory of polyhedra using finite topological spaces. We define the concept of collapse of a finite space and prove that this new notion corresponds exactly to the concept of a simplicial…

Algebraic Topology · Mathematics 2007-05-23 Jonathan Ariel Barmak , Elias Gabriel Minian

Preliminary results toward the analysis of the Hamiltonian structure of multifield theories describing complex materials are mustered: we involve the invariance under the action of a general Lie group of the balance of substructural…

Mathematical Physics · Physics 2007-05-23 Gianfranco Capriz , Paolo Maria Mariano

We extend the framework of modular invariant supersymmetric theories to encompass invariance under more general discrete groups $\Gamma$, that allow the presence of several moduli and make connection with the theory of automorphic forms.…

High Energy Physics - Theory · Physics 2021-02-03 Gui-Jun Ding , Ferruccio Feruglio , Xiang-Gan Liu

This paper introduces a speciation principle for neuroevolution where evolving networks are grouped into species based on the number of hidden neurons, which is indicative of the complexity of the search space. This speciation principle is…

Neural and Evolutionary Computing · Computer Science 2020-10-13 Alexander Hadjiivanov , Alan Blair

We establish a Quillen equivalence relating the homotopy theory of Segal operads and the homotopy theory of simplicial operads, from which we deduce that the homotopy coherent nerve functor is a right Quillen equivalence from the model…

Algebraic Topology · Mathematics 2014-02-26 Denis-Charles Cisinski , Ieke Moerdijk

Both simplicial sets and simplicial spaces are used pervasively in homotopy theory as presentations of spaces, where in both cases we extract the "underlying space" by taking geometric realization. We have a good handle on the category of…

Algebraic Topology · Mathematics 2015-10-20 Aaron Mazel-Gee

This paper is a survey of our work based on the stratified Morse theory of Goresky and MacPherson. First we discuss the Morse theory of Euclidean space stratified by an arrangement. This is used to show that the complement of a complex…

Algebraic Geometry · Mathematics 2007-05-23 Daniel C. Cohen , Peter Orlik

Real-world learning tasks often encounter uncertainty due to covariate shift and noisy or inconsistent labels. However, existing robust learning methods merge these effects into a single distributional uncertainty set. In this work, we…

Methodology · Statistics 2026-03-17 Varun Venkatesh , Eyke Hüllermeier , Bernd Bischl , Mina Rezaei

We study configuration space integral formulas for Milnor's homotopy link invariants, showing that they are in correspondence with certain linear combinations of trivalent trees. Our proof is essentially a combinatorial analysis of a…

Algebraic Topology · Mathematics 2021-06-23 Robin Koytcheff , Ismar Volic

Modular invariance is a fundamental symmetry in string compactifications, constraining both the structure of the effective theory and the dynamics of moduli and matter fields. It has also gained renewed importance in the context of…

Group equivariant convolutional networks (GCNNs) endow classical convolutional networks with additional symmetry priors, which can lead to a considerably improved performance. Recent advances in the theoretical description of GCNNs revealed…

Machine Learning · Computer Science 2021-01-22 Leon Lang , Maurice Weiler
‹ Prev 1 4 5 6 7 8 10 Next ›