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Related papers: On the predictive power of Local Scale Invariance

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The relativistic theory of structure formation in cosmology is based mainly on linear perturbations about a homogeneous background. But we are now driven to understand the theory of higher-order perturbations in full detail, both from…

Cosmology and Nongalactic Astrophysics · Physics 2011-08-24 Chris Clarkson

In order to check on a recent suggestion that local scale invariance [M.Henkel et al. Phys.Rev.Lett. {\bf 87}, 265701 (2001)] might hold when the dynamics is of Gaussian nature, we have carried out the measurement of the response function…

Statistical Mechanics · Physics 2007-05-23 Eugenio Lippiello , Federico Corberi , Marco Zannetti

In four dimensional unitary scale invariant theories, arguments based on the proof of the a-theorem suggest that the trace of the energy-momentum tensor T vanishes when the momentum is light-like, p^2=0. We show that there exists a local…

High Energy Physics - Theory · Physics 2014-03-21 Kazuya Yonekura

Despite the wide use of explainability techniques to attempt to understand the behavior of Artificial Intelligence (AI), the generated explanations may not always be reliable. An explanation can appear plausible to humans but fail to…

Machine Learning · Computer Science 2026-05-28 Tomás Pereira , João Vitorino , Eva Maia , Isabel Praça

The \textit{local learning coefficient} (LLC) is a principled way of quantifying model complexity, originally derived in the context of Bayesian statistics using singular learning theory (SLT). Several methods are known for numerically…

Machine Learning · Computer Science 2024-10-01 Zach Furman , Edmund Lau

Reliable uncertainty quantification at unobserved spatial locations, especially in the presence of complex and heterogeneous datasets, remains a core challenge in spatial statistics. Traditional approaches like Kriging rely heavily on…

Machine Learning · Statistics 2025-02-18 Hanyang Jiang , Yao Xie

We present an extension of local sensitivity analysis, also referred to as the perturbation approach for uncertainty quantification, to Bayesian inverse problems. More precisely, we show how moments of random variables with respect to the…

Numerical Analysis · Mathematics 2026-04-06 Jürgen Dölz , David Ebert

Conformal invariance powerfully constrains the critical behavior of two-dimensional classical systems with short-range interactions and the critical theories in two-dimensions are parametrized by a dimensional number, termed central charge…

Quantum Physics · Physics 2017-06-15 Bo-Bo Wei

Analogical reasoning relies on conceptual abstractions, but it is unclear whether Large Language Models (LLMs) harbor such internal representations. We explore distilled representations from LLM activations and find that function vectors…

Computation and Language · Computer Science 2025-03-06 Gustaw Opiełka , Hannes Rosenbusch , Claire E. Stevenson

Being a powerful tool for linear time-invariant (LTI) systems, system response analysis can also be applied to the so-called linear space-invariant (LSI) but time-varying systems, which is a dual of the conventional LTI problems. In this…

Optics · Physics 2022-08-10 Wending Mai , Jingwei Xu , Arkaprovo Das , Douglas H. Werner

Inhomogeneities in real-world data, e.g., due to changes in the observation noise level or variations in the structural complexity of the source function, pose a unique set of challenges for statistical inference. Accounting for them can…

Machine Learning · Computer Science 2023-12-13 Danny Panknin , Stefan Chmiela , Klaus-Robert Müller , Shinichi Nakajima

Statistical systems near a classical critical point have been intensively studied both from theoretical and experimental points of view. In particular, correlation functions are of relevance in comparing theoretical models with the…

High Energy Physics - Theory · Physics 2018-05-25 Andrea Amoretti , Nicodemo Magnoli

In the context of integrated correlators in $\mathcal{N}=4$ SYM, we study the 2-point functions of local operators with a superconformal line defect. Starting from the mass-deformed $\mathcal{N}=2^*$ theory in presence of a…

High Energy Physics - Theory · Physics 2023-11-30 M. Billo' , M. Frau , F. Galvagno , A. Lerda

We generalize the previous study on the application of variational autoencoders to the two-dimensional Ising model to a system with anisotropy. Due to the self-duality property of the system, the critical points can be located exactly for…

Disordered Systems and Neural Networks · Physics 2023-10-31 Anshumitra Baul , Nicholas Walker , Juana Moreno , Ka-Ming Tam

The time-dependent scaling of the two-time autocorrelation function of spin systems without disorder undergoing phase-ordering kinetics is considered. Its form is shown to be determined by an extension of dynamical scaling to a local…

Statistical Mechanics · Physics 2007-05-23 Malte Henkel , Alan Picone , Michel Pleimling

With the advancement of technology for artificial intelligence (AI) based solutions and analytics compute engines, machine learning (ML) models are getting more complex day by day. Most of these models are generally used as a black box…

Machine Learning · Computer Science 2022-10-11 P. Sai Ram Aditya , Mayukha Pal

Extending the concept of multi-selfsimilar random field we study multi-scale invariant (MSI) fields which have component-wise discrete scale invariant property. Assuming scale parameters as $\lambda_i>1$, $i=1,\ldots,d$ and the parameter…

Applications · Statistics 2020-06-11 H. Ghasemi , S. Rezakhah , N. Modarresi

The local scale invariance has been investigated in the nonequilibrium kinetic Ising model exhibiting absorbing phase transition of PC type in 1+1 dimension. Numerical evidence has been found for the satisfaction of this symmetry and…

Statistical Mechanics · Physics 2009-11-11 Geza Odor

A new realization of the conformal algebra is studied which mimics the behaviour of a statistical system on a discrete albeit infinite lattice. The two-point function is found from the requirement that it transforms covariantly under this…

Statistical Mechanics · Physics 2008-11-26 Malte Henkel , Dragi Karevski

This paper is concerned with robust performance criteria for linear continuous time invariant stochastic systems driven by statistically uncertain random processes. The uncertainty is understood as the deviation of imprecisely known…

Optimization and Control · Mathematics 2019-03-06 Igor G. Vladimirov
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