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We propose tensorial neural networks (TNNs), a generalization of existing neural networks by extending tensor operations on low order operands to those on high order ones. The problem of parameter learning is challenging, as it corresponds…

Machine Learning · Statistics 2018-12-11 Jiahao Su , Jingling Li , Bobby Bhattacharjee , Furong Huang

We extend recent work by Howie, Mathews and Purcell to simplify the calculation of A-polynomials for any family of hyperbolic knots related by twisting. The main result follows from the observation that equations defining the deformation…

Geometric Topology · Mathematics 2023-08-22 Em K. Thompson

We formulate the holographic principle for knots and links. For the "space" of all knots and links, torus knots T(2m+1,2) and torus links L(2m,2) play the role of the "boundary" of this space. Using the holographic principle, we find the…

Geometric Topology · Mathematics 2015-11-17 A. M. Pavlyuk

Knotted molecules occur naturally and are designed by scientists to gain special biological and material properties. Understanding and utilizing knotting require efficient methods to recognize and generate knotted structures, which are…

Computational Physics · Physics 2025-01-23 Zhiyu Zhang , Yongjian Zhu , Liang Dai

Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and…

Data Structures and Algorithms · Computer Science 2014-01-21 Aditya Bhaskara , Moses Charikar , Ankur Moitra , Aravindan Vijayaraghavan

It is a well known result from Thistlethwaite that the Jones polynomial of a non-split alternating link is alternating. We find the right generalization of this result to the case of non-split alternating tangles. More specifically: the…

Geometric Topology · Mathematics 2014-03-06 Hernando Burgos-Soto

Decompositions of tensors into factor matrices, which interact through a core tensor, have found numerous applications in signal processing and machine learning. A more general tensor model which represents data as an ordered network of…

Numerical Analysis · Computer Science 2016-09-30 Anh-Huy Phan , Andrzej Cichocki , Andre Uschmajew , Petr Tichavsky , George Luta , Danilo Mandic

We give an explicit formula for the Jones polynomial of any rational link in terms of the denominators of the canonical continued fraction of the slope of the given rational link.

Geometric Topology · Mathematics 2014-06-18 Khaled Qazaqzeh , Moh'd Yasein , Majdoleen Abu-Qamar

In a previous paper (q-alg/9501022) we suggested some algorithms that could be useful in solving the problem of knot classification. Here we continue this discussion by answering questions raised in that paper and by commenting on practical…

q-alg · Mathematics 2008-02-03 Charilaos Aneziris

This paper is a brief overview of recent results by the authors relating colored Jones polynomials to geometric topology. The proofs of these results appear in the papers [arXiv:1002.0256] and [arXiv:1108.3370], while this survey focuses on…

Geometric Topology · Mathematics 2014-04-01 David Futer , Efstratia Kalfagianni , Jessica S. Purcell

In this paper we propose a novel efficient algorithm for calculating winding numbers, aiming at counting the number of roots of a given polynomial in a convex region on the complex plane. This algorithm can be used for counting and…

Numerical Analysis · Mathematics 2019-08-20 Vitaly Zaderman , Liang Zhao

Symmetry of geometrical figures is reflected in regularities of their algebraic invariants. Algebraic regularities are often preserved when the geometrical figure is topologically deformed. The most natural, intuitively simple but…

Geometric Topology · Mathematics 2007-05-23 Jozef H. Przytycki

We prove an explicit cabling formula for the colored Jones polynomial. As an application we prove the volume conjecture for all zero volume knots and links, i.e. all knots and links that are obtained from the unknot by repeated cabling and…

Geometric Topology · Mathematics 2008-07-18 Roland van der Veen

Tensor networks (TNs) enable compact representations of large tensors through shared parameters. Their use in probabilistic modeling is particularly appealing, as probabilistic tensor networks (PTNs) allow for tractable computation of…

Machine Learning · Computer Science 2025-10-02 Marawan Gamal Abdel Hameed , Guillaume Rabusseau

In this paper we discuss an approach to calculate knot polynomials on a photonic processor. Calculations of knot polynomials is a computationally difficult problem and therefore it is interesting to use new advanced calculation methods to…

Quantum Physics · Physics 2024-05-07 Ivan Dyakonov , Ilya Kondratyev , Sergey Mironov , Andrey Morozov

Factorization machines and polynomial networks are supervised polynomial models based on an efficient low-rank decomposition. We extend these models to the multi-output setting, i.e., for learning vector-valued functions, with application…

Machine Learning · Statistics 2017-11-07 Mathieu Blondel , Vlad Niculae , Takuma Otsuka , Naonori Ueda

In previous joint work with Frohman and Lofaro a noncommutative generalization of the A-polynomial of a knot was introduced, consisting of a finitely generated ideal of polynomials (the noncommutative A-ideal) in the quantum plane. The…

Quantum Algebra · Mathematics 2007-05-23 Razvan Gelca

The slope conjecture gives a precise relation between the degree of the colored Jones polynomial of a knot and the boundary slopes of essential surfaces in the knot complement. In this note we propose a generalization of the slope…

Geometric Topology · Mathematics 2015-01-15 Roland van der Veen

The theory of the Kauffman bracket, which describes the Jones polynomial as a sum over closed circles formed by the planar resolution of vertices in a knot diagram, can be straightforwardly lifted from sl(2) to sl(N) at arbitrary N -- but…

High Energy Physics - Theory · Physics 2024-10-07 A. Anokhina , E. Lanina , A. Morozov

It is well known that tensor network regression models operate on an exponentially large feature space, but questions remain as to how effectively they are able to utilize this space. Using a polynomial featurization, we propose the…

Machine Learning · Computer Science 2023-01-27 Ian Convy , K. Birgitta Whaley