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In this paper we develop a graded tilting theory for gauged Landau-Ginzburg models of regular sections in vector bundles over projective varieties. Our main theoretical result describes - under certain conditions - the bounded derived…

Algebraic Geometry · Mathematics 2021-06-08 Christian Okonek , Andrei Teleman

In this survey article we introduce the notion of frontals, which provides a class of generalised submanifolds with singularities but with well-defined tangent spaces. We present a review of basic theory and known studies on frontals in…

Differential Geometry · Mathematics 2016-09-05 Goo Ishikawa

The paper glosses different forms of an introducing of higher order tangent-like functors, especially functors derived from higher order nonholonomic tangent functors. A special attention is devoted to higher order osculating bundles: their…

Differential Geometry · Mathematics 2012-02-15 Miroslav Kureš

In order to provide a good categorical setting to the many different spaces of fields arising in the description of physical theories, a pedagogical introduction to the categorical notion of smooth sets is provided and some simple…

Mathematical Physics · Physics 2025-10-24 Alberto Ibort , Arnau Mas

We introduce a class of diffeological spaces, called elastic, on which the left Kan extension of the tangent functor of smooth manifolds defines an abstract tangent functor in the sense of Rosicky. On elastic spaces there is a natural…

Differential Geometry · Mathematics 2023-01-09 Christian Blohmann

Domain adaptation aims to transfer the knowledge learned on (data-rich) source domains to (low-resource) target domains, and a popular method is invariant representation learning, which matches and aligns the data distributions on the…

Information Retrieval · Computer Science 2023-11-01 Ruicheng Xian , Honglei Zhuang , Zhen Qin , Hamed Zamani , Jing Lu , Ji Ma , Kai Hui , Han Zhao , Xuanhui Wang , Michael Bendersky

We discover a fundamental exterior differential system of Riemannian geometry; indeed, an intrinsic and invariant global system of differential forms of degree $n$ associated to any given oriented Riemannian manifold $M$ of dimension $n+1$.…

Differential Geometry · Mathematics 2022-11-02 Rui Albuquerque

This paper is motivated from a fundamental curiosity on what defines a category of object shapes. For example, we may have the common knowledge that a plane has wings, and a chair has legs. Given the large shape variations among different…

Computer Vision and Pattern Recognition · Computer Science 2020-12-15 Chaozheng Wu , Lin Sun , Xun Xu , Kui Jia

In general terms, Gelfand duality refers to a correspondence between a geometric, topological, or analytical category, and an algebraic category. For example, in smooth differential geometry, Gelfand duality refers to the topological…

Differential Geometry · Mathematics 2020-09-23 Andrew D. Lewis

A neural population responding to multiple appearances of a single object defines a manifold in the neural response space. The ability to classify such manifolds is of interest, as object recognition and other computational tasks require a…

Disordered Systems and Neural Networks · Physics 2022-08-30 Uri Cohen , Haim Sompolinsky

The complexity of a learning task is increased by transformations in the input space that preserve class identity. Visual object recognition for example is affected by changes in viewpoint, scale, illumination or planar transformations.…

Computer Vision and Pattern Recognition · Computer Science 2017-03-16 Andrea Tacchetti , Stephen Voinea , Georgios Evangelopoulos

Contrastive visual pretraining based on the instance discrimination pretext task has made significant progress. Notably, recent work on unsupervised pretraining has shown to surpass the supervised counterpart for finetuning downstream…

Computer Vision and Pattern Recognition · Computer Science 2021-01-20 Nanxuan Zhao , Zhirong Wu , Rynson W. H. Lau , Stephen Lin

We develop the theory of probabilistic variants of the one-category and diagonal topological complexity, which bound the classical LS-category and topological complexity from below. Unlike any other classical or probabilistic invariants,…

Algebraic Topology · Mathematics 2025-12-16 Ekansh Jauhari , John Oprea

We combine multi-task learning and semi-supervised learning by inducing a joint embedding space between disparate label spaces and learning transfer functions between label embeddings, enabling us to jointly leverage unlabelled data and…

Computation and Language · Computer Science 2018-04-10 Isabelle Augenstein , Sebastian Ruder , Anders Søgaard

The popular view according to which Category theory provides a support for Mathematical Structuralism is erroneous. Category-theoretic foundations of mathematics require a different philosophy of mathematics. While structural mathematics…

History and Overview · Mathematics 2010-02-20 Andrei Rodin

Contrastive learning is among the most popular and powerful approaches for self-supervised representation learning, where the goal is to map semantically similar samples close together while separating dissimilar ones in the latent space.…

Machine Learning · Statistics 2025-12-03 Ali Alvandi , Mina Rezaei

We construct a new category of vector spaces which contains both the standard category of vector spaces and Grassmannians. Its space of objects classifies vector bundles, its space of morphisms classifies bundle isomorphisms, and it can be…

Algebraic Topology · Mathematics 2017-11-09 Yi-Sheng Wang

We study the cluster categories arising from marked surfaces (with punctures and non-empty boundaries). By constructing skewed-gentle algebras, we show that there is a bijection between tagged curves and string objects. Applications include…

Representation Theory · Mathematics 2019-02-20 Yu Qiu , Yu Zhou

We review the concept of a graded bundle as a natural generalisation of a vector bundle. Such geometries are particularly nice examples of more general graded manifolds. With hindsight there are many examples of graded bundles that appear…

Differential Geometry · Mathematics 2016-05-12 Andrew J. Bruce , K. Grabowska , J. Grabowski

Regressing rotations on SO(3) manifold using deep neural networks is an important yet unsolved problem. The gap between the Euclidean network output space and the non-Euclidean SO(3) manifold imposes a severe challenge for neural network…

Computer Vision and Pattern Recognition · Computer Science 2022-03-31 Jiayi Chen , Yingda Yin , Tolga Birdal , Baoquan Chen , Leonidas Guibas , He Wang