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A promising approach to investigating high-dimensional problems is to identify their intrinsically low-dimensional features, which can be achieved through recently developed techniques for effective low-dimensional representation of…

Analysis of PDEs · Mathematics 2025-06-02 Zeyu Jin , Ruo Li

The reduction of dynamical systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically performed in an exact manner - as is the case with…

Optimization and Control · Mathematics 2007-07-26 Paulo Tabuada , Aaron D. Ames , Agung Julius , George J. Pappas

We offer a systematic account of decomposition of quantum systems into parts. Different decompositions (structures) are mutually linked via the proper linear canonical transformations. Different kinds of structures, as well as their…

Quantum Physics · Physics 2014-06-03 Jasmina Jeknic-Dugic , Momir Arsenijevic , Miroljub Dugic

We have recently introduced a realistic, covariant, interpretation for the reduction process in relativistic quantum mechanics. The basic problem for a covariant description is the dependence of the states on the frame within which collapse…

Quantum Physics · Physics 2008-11-26 Rodolfo Gambini , Rafael A. Porto

The understanding of the behaviour of systems of identical composite bosons has progressed significantly in connection with the analysis of the entanglement between constituents and the development of coboson theory. The basis of these…

Transformer models contain substantial internal redundancy arising from coordinate-dependent representations and continuous symmetries, in model space and in head space, respectively. While recent approaches address this by explicitly…

Machine Learning · Computer Science 2026-02-24 J. François , L. Ravera

Shape inference is classically ill-posed, because it involves a map from the (2D) image domain to the (3D) world. Standard approaches regularize this problem by either assuming a prior on lighting and rendering or restricting the domain,…

Computer Vision and Pattern Recognition · Computer Science 2020-08-21 Steven W Zucker

This paper serves as a preparation of work that focuses on extracting cosmological sectors from Loop Quantum Gravity. We start with studying the extraction of subsystems from classical systems. A classical Hamiltonian system can be reduced…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Tim Koslowski

Theory revision integrates inductive learning and background knowledge by combining training examples with a coarse domain theory to produce a more accurate theory. There are two challenges that theory revision and other theory-guided…

Artificial Intelligence · Computer Science 2008-02-03 S. K. Donoho , L. A. Rendell

By means of simple models in a flat spacetime manifold we examine some of the issues that arise when quantizing interacting quantum fields in multi-metric backgrounds. In particular we investigate the maintenance of a causal structure in…

High Energy Physics - Theory · Physics 2015-06-15 I. T. Drummond

With time, machine learning models have increased in their scope, functionality and size. Consequently, the increased functionality and size of such models requires high-end hardware to both train and provide inference after the fact. This…

Machine Learning · Computer Science 2021-09-07 Arhum Ishtiaq , Sara Mahmood , Maheen Anees , Neha Mumtaz

A theorem of Laman gives a combinatorial characterisation of the graphs that admit a realisation as a minimally rigid generic bar-joint framework in $\bR^2$. A more general theory is developed for frameworks in $\bR^3$ whose vertices are…

Combinatorics · Mathematics 2012-10-05 A. Nixon , J. C. Owen , S. C. Power

Chemical kinetic models in terms of ordinary differential equations correspond to finite dimensional dissipative dynamical systems involving a multiple time scale structure. Most dimension reduction approaches aimed at a slow…

Dynamical Systems · Mathematics 2014-10-27 Dirk Lebiedz , Jonas Unger

Associated to any finite metric space are a large number of objects and quantities which provide some degree of structural or geometric information about the space. In this paper we show that in the setting of subsets of weighted Hamming…

Functional Analysis · Mathematics 2024-09-19 Ian Doust , Anthony Weston

Recent progress concerning regularization of supersymmetric theories is reviewed. Dimensional reduction is reformulated in a mathematically consistent way, and an elegant and general method is presented that allows to study the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Dominik Stöckinger

Different notions on regularity of sets and of collection of sets play an important role in the analysis of the convergence of projection algorithms in nonconvex scenarios. While some projection algorithms can be applied to feasibility…

Optimization and Control · Mathematics 2023-10-24 Rubén Campoy

Mode-based model-reduction is used to reduce the degrees of freedom of high dimensional systems, often by describing the system state by a linear combination of spatial modes. Transport dominated phenomena, ubiquitous in technical and…

Numerical Analysis · Mathematics 2020-02-28 Julius Reiss

Minimal surfaces and domain walls play important roles in various contexts of spacetime physics as well as material science. In this paper, we first review the Bernstein conjecture, which asserts that a plane is the only globally well…

High Energy Physics - Theory · Physics 2009-09-28 Gary W. Gibbons , Kei-ichi Maeda , Umpei Miyamoto

We define a computational type theory combining the contentful equality structure of cartesian cubical type theory with internal parametricity primitives. The combined theory supports both univalence and its relational equivalent, which we…

Logic in Computer Science · Computer Science 2023-06-22 Evan Cavallo , Robert Harper

This paper proposes a generalized framework with joint normalization which learns lower-dimensional subspaces with maximum discriminative power by making use of the Riemannian geometry. In particular, we model the similarity/dissimilarity…

Computer Vision and Pattern Recognition · Computer Science 2017-11-20 Tianci Liu , Zelin Shi , Yunpeng Liu