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We give characterizations for homogeneous and inhomogeneous Besov-Lizorkin-Triebel spaces in terms of continuous local means for the full range of parameters. In particular, we prove characterizations in terms of Lusin functions and spaces…

Functional Analysis · Mathematics 2010-09-29 Tino Ullrich

Prior work on partial labels learning (PLL) has shown that learning is possible even when each instance is associated with a bag of labels, rather than a single accurate but costly label. However, the necessary conditions for learning with…

Machine Learning · Statistics 2026-03-23 Nicolas A. Errandonea , Santiago Mazuelas , Jose A. Lozano , Sanjoy Dasgupta

We introduce a numerical procedure to investigate the spectrum of massive modes and its contribution for gravity localization on thick branes. After considering a model with an analytically known Schroedinger potential, we present the…

High Energy Physics - Theory · Physics 2009-04-03 D. Bazeia , A. R. Gomes , L. Losano

Adding interpretability to multivariate methods creates a powerful synergy for exploring complex physical systems with higher order correlations while bringing about a degree of clarity in the underlying dynamics of the system.

High Energy Physics - Phenomenology · Physics 2022-05-04 Christophe Grojean , Ayan Paul , Zhuoni Qian , Inga Strümke

The increasing adoption of machine learning tools has led to calls for accountability via model interpretability. But what does it mean for a machine learning model to be interpretable by humans, and how can this be assessed? We focus on…

Machine Learning · Computer Science 2019-08-06 Dylan Slack , Sorelle A. Friedler , Carlos Scheidegger , Chitradeep Dutta Roy

In this paper we review results of Anderson localization for different random families of operators which enter in the framework of random quasi-one-dimensional models. We first recall what is Anderson localization from both physical and…

Mathematical Physics · Physics 2023-07-04 Hakim Boumaza

We establish the isomorphism between a nonlinear $\sigma$-model and the abelian gauge theory on an arbitrary curved background, which allows us to derive integrable models and the corresponding Lax representations from gauge theoretical…

Mathematical Physics · Physics 2009-09-25 Hao-Shiung Lin , Oktay K. Pashaev , Shi-Shyr Roan

We establish the isomorphism between a nonlinear $\sigma$-model and the abelian gauge theory on an arbitrary curved background, which allows us to derive integrable models and the corresponding Lax representations from gauge theoretical…

High Energy Physics - Theory · Physics 2008-02-03 Shao-shiung Lin , Oktay K. Pashaev , Shi-shyr Roan

We prove the compatibility at places dividing l of the local and global Langlands correspondences for the l-adic Galois representations associated to regular algebraic essentially (conjugate) self-dual cuspidal automorphic representations…

Number Theory · Mathematics 2011-05-12 Thomas Barnet-Lamb , Toby Gee , David Geraghty , Richard Taylor

We propose a new interpretation of doubly special relativity (DSR) based on the distinction between the momentum and the translation generators in its phase space realization. We also argue that the implementation of DSR theories does not…

General Relativity and Quantum Cosmology · Physics 2009-02-12 S. Mignemi

Stationary to pulsating soliton bifurcation analysis of the complex Ginzburg-Landau equation (CGLE) is presented. The analysis is based on a reduction from an infinite-dimensional dynamical dissipative system to a finite-dimensional model.…

Pattern Formation and Solitons · Physics 2009-11-11 E. N. Tsoy , N. Akhmediev

We develop a linear systems theory that coincides with the existing theories for continuous and discrete dynamical systems, but that also extends to linear systems defined on nonuniform time domains. The approach here is based on…

Optimization and Control · Mathematics 2009-03-03 John M. Davis , Ian A. Gravagne , Billy J. Jackson , Robert J. Marks

Existing self-supervised learning (SSL) methods primarily learn object-invariant representations but often neglect the spatial structure and relationships among object parts. To address this limitation, we introduce Spatial Prediction (SP),…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yang Shen , Yusen Cai , Weronika Hryniewska-Guzik , Qing Lin , Mengmi Zhang

We examine the locality assumption of Bell's theorem in three steps of EPRB experiment. Depending on the context, locality is embodied in the conditions of separability, local causality, factorizability, relativistic causality, and…

Quantum Physics · Physics 2017-04-28 Afshin Shafiee , Farhad Taher Ghahramani

In this study, we present a novel clinical decision support system and discuss its interpretability-related properties. It combines a decision set of rules with a machine learning scheme to offer global and local interpretability. More…

Methodology · Statistics 2021-07-16 Francisco Valente , Simão Paredes , Jorge Henriques

While initial versions of Bell's theorem captured the notion of locality with the assumption of factorizability, in later presentations, Bell argued that factorizability could be derived from the more fundamental principle of local…

Quantum Physics · Physics 2022-04-12 G. S. Ciepielewski , E. Okon

I examine whether Nelson's stochastic formulation of Schr\"{o}dinger equation could be derived from a phase space process through a colored noise smoothing. If this conjecture is true, it would yield a local stochastic hidden variable…

Quantum Physics · Physics 2022-04-08 Can Gokler

Accepting validity of self-consistent theory of localization by Vollhardt and Woelfle, we derive the relations of finite-size scaling for different parameters characterizing the level statistics. The obtained results are compared with the…

Disordered Systems and Neural Networks · Physics 2015-06-18 I. M. Suslov

Usually the 'hidden variables' of Bell's theorem are supposed to describe the pair of Bell particles. Here a semantic shift is proposed, namely to attach the hidden variables to a stochastic medium or field in which the particles move. It…

Quantum Physics · Physics 2017-01-24 Louis Vervoort

The widespread adoption of deep learning models in computer vision has intensified concerns about interpretability. Despite strong performance, these models are often treated as black boxes, with limited systematic investigation of their…

Machine Learning · Computer Science 2026-05-13 Konstantinos P. Panousis , Diego Marcos
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