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Several authors have recently constructed characteristic classes for classes of infinite rank vector bundles appearing in topology and physics. These include the tangent bundle to the space of maps between closed manifolds, the infinite…

K-Theory and Homology · Mathematics 2011-07-26 Andres Larrain-Hubach

Bundling, the practice of jointly selling two or more products at a discount, is a widely used strategy in industry and a well examined concept in academia. Historically, the focus has been on theoretical studies in the context of…

Machine Learning · Computer Science 2020-02-04 Madhav Kumar , Dean Eckles , Sinan Aral

In an unpublished preprint, A. King conjectured that there are tilting bundles over projective varieties which are obtained as invariant quotients of affine spaces for linear actions of reductive groups. The goal of this paper is to give…

Algebraic Geometry · Mathematics 2009-06-19 Mihai Halic

We introduce probability estimation, a broadly applicable framework to certify randomness in a finite sequence of measurement results without assuming that these results are independent and identically distributed. Probability estimation…

Quantum Physics · Physics 2018-11-30 Yanbao Zhang , Emanuel Knill , Peter Bierhorst

For a family of unital free *-algebras with a family of states on them, we construct a sequence of noncommutative probability spaces, which are tensor product algebras with tensor product states and which approximate the free product of…

Quantum Algebra · Mathematics 2014-07-25 Romuald Lenczewski

Finite frames can be viewed as mass points distributed in $N$-dimensional Euclidean space. As such they form a subclass of a larger and rich class of probability measures that we call probabilistic frames. We derive the basic properties of…

Probability · Mathematics 2017-09-04 Martin Ehler , Kasso A. Okoudjou

Incorporating constraints is a major concern in probabilistic machine learning. A wide variety of problems require predictions to be integrated with reasoning about constraints, from modelling routes on maps to approving loan predictions.…

Machine Learning · Computer Science 2020-01-31 Ioannis Papantonis , Vaishak Belle

Several intrinsic topological ways to encode connections on vector bundles on smooth complex algebraic curves will be described. In particular the notion of {\em Stokes decompositions} will be formalised, as a convenient intermediate…

Algebraic Geometry · Mathematics 2021-05-19 Philip Boalch

Rigorous guarantees about the performance of predictive algorithms are necessary in order to ensure their responsible use. Previous work has largely focused on bounding the expected loss of a predictor, but this is not sufficient in many…

Machine Learning · Computer Science 2022-12-29 Jake C. Snell , Thomas P. Zollo , Zhun Deng , Toniann Pitassi , Richard Zemel

We study random, finite-dimensional, ungraded chain complexes over a finite field and show that for a uniformly distributed differential a complex has the smallest possible homology with the highest probability: either zero or…

Combinatorics · Mathematics 2017-07-05 Viktor L. Ginzburg , Dmitrii V. Pasechnik

In the framework of Category Theory, we study the association between finite--dimensional representations of a compact quantum group and quantum vector bundles with linear connections for a given quantum principal bundle with a principal…

Quantum Algebra · Mathematics 2025-05-21 Gustavo Amilcar Saldaña Moncada

Expectiles are statistical parameters which also provide a class of sublinear risk measures in finance. They are solutions of continuous optimization problems. The corresponding first order condition provides two different fixed point…

Statistics Theory · Mathematics 2025-09-03 Thi Khanh Linh Ha , Andreas Heinrich Hamel , Daniel Kostner

In this paper we propose a finite-dimensional and deterministic approach to the study of invariant sets of certain nonautonomous differential inclusions naturally arising in the context of random and control dynamical systems, as well as in…

Dynamical Systems · Mathematics 2026-04-30 Konstantinos Kourliouros , Iacopo P. Longo , Martin Rasmussen

We study quotients of multi-graded bundles, including double vector bundles. Among other things, we show that any such quotient fits into a tower of affine bundles. Applications of the theory include a construction of normal bundles for…

Differential Geometry · Mathematics 2024-11-28 Eckhard Meinrenken

As physics searches for invariants in observations, this paper looks for invariants of probabilistic observation without assuming physical structure. Structure emerges from the basic assumption of science that new information shall lead to…

Quantum Physics · Physics 2007-05-23 Johann Summhammer

A subbundle of variable dimension inside the tangent bundle of a smooth manifold is called a smooth distribution if it is the pointwise span of a family of smooth vector fields. We prove that all such distributions are finitely generated,…

Differential Geometry · Mathematics 2021-01-28 Lance D. Drager , Jeffrey M. Lee , Efton Park , Ken Richardson

Tangent categories are categories equipped with a tangent functor: an endofunctor with certain natural transformations which make it behave like the tangent bundle functor on the category of smooth manifolds. They provide an abstract…

Category Theory · Mathematics 2017-03-10 J. R. B. Cockett , G. S. H. Cruttwell

Conditionals play a key role in different areas of logic and probabilistic reasoning, and they have been studied and formalized from different angles. In this paper we focus on the de Finetti's notion of conditional as a three-valued…

Logic · Mathematics 2022-05-09 Tommaso Flaminio , Angelo Gilio , Lluis Godo , Giuseppe Sanfilippo

The theory of linear transports along paths in vector bundles, generalizing the parallel transports generated by linear connections, is developed. The normal frames for them are defined as ones in which their matrices are the identity…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Bozhidar Z. Iliev

For better learning, large datasets are often split into small batches and fed sequentially to the predictive model. In this paper, we study such batch decompositions from a probabilistic perspective. We assume that data points (possibly…

Machine Learning · Computer Science 2025-04-10 Ghurumuruhan Ganesan
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