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We present an extension of the identity method initially introduced for particle yield fluctuation studies towards measurements of differential correlations. The extension is developed and illustrated in the context of measurements of the…

Data Analysis, Statistics and Probability · Physics 2018-07-25 Claude Pruneau , Alice Ohlson

Let $\pi_n$ be a uniformly chosen random permutation on $[n]$. Using an analysis of the probability that two overlapping consecutive $k$-permutations are order isomorphic, the authors of a recent paper showed that the expected number of…

Combinatorics · Mathematics 2024-08-07 Anant Godbole , Hannah Swickheimer

We investigate the relationship between persistent currents in multi-channel rings containing an embedded scatterer and the conductance through the same scatterer attached to leads. The case of two uncoupled channels corresponds to a…

Constrained sequential pattern mining aims at identifying frequent patterns on a sequential database of items while observing constraints defined over the item attributes. We introduce novel techniques for constraint-based sequential…

Machine Learning · Computer Science 2019-01-01 Amin Hosseininasab , Willem-Jan van Hoeve , Andre A. Cire

We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate. We analyze the performance of two classes of estimators, namely the…

Neural and Evolutionary Computing · Computer Science 2017-03-24 Abbas Kazemipour , Min Wu , Behtash Babadi

The paper introduces new types of nonlinear correlations between bivariate data sets and derives nonlinear auto-correlations on the same data set. These auto-correlations are of different types to match signals with different types of…

Chaotic Dynamics · Physics 2014-09-23 Sanjay Kumar Palit , Sayan Mukherjee , D. K. Bhattacharya

A set of probabilistic predictions is well calibrated if the events that are predicted to occur with probability p do in fact occur about p fraction of the time. Well calibrated predictions are particularly important when machine learning…

Machine Learning · Statistics 2014-01-14 Mahdi Pakdaman Naeini , Gregory F. Cooper , Milos Hauskrecht

This paper proposes multivariate copula models for hierarchical data. They account for two types of correlation: one is between variables measured on the same unit and the other is a correlation between units in the same cluster. This model…

Methodology · Statistics 2023-04-24 Talagbe Gabin Akpo , Louis-Paul Rivest

Two particle correlations are studied in the reaction plane of peripheral relativistic heavy ion reactions where the initial state has substantial angular momentum. The earlier predicted rotation effect and Kelvin Helmholtz Instability,…

Nuclear Theory · Physics 2013-05-06 L. P. Csernai , S. Velle

The study of particle correlations is an important instrument to understand the nature of relativistic heavy ion collisions. Using a wealth of new data available from the recent heavy ion runs of Large Hadron Collider at CERN it becomes…

Nuclear Experiment · Physics 2019-08-12 Alexander Milov

Renaud Parentani has given a vast contribution to the development of gravitational analogue models as tools to explore various important aspects of general relativity and of quantum field theory in curved space-time. In these systems,…

Quantum Gases · Physics 2025-04-23 Alessia Biondi , Maria Luisa Chiofalo , Massimo Mannarelli , Silvia Trabucco

We present a method for studying the excitations of low-dimensional quantum spin systems based on the Jordan-Wigner transformation. Using an extended RPA-scheme we calculate the correlation function of neighboring spin flips which well…

Strongly Correlated Electrons · Physics 2013-05-29 Tamara S. Nunner , Thilo Kopp

Linear probes are a promising approach for monitoring AI systems for deceptive behaviour. Previous work has shown that a linear classifier trained on a contrastive instruction pair and a simple dataset can achieve good performance. However,…

Artificial Intelligence · Computer Science 2026-02-03 Vikram Natarajan , Devina Jain , Shivam Arora , Satvik Golechha , Joseph Bloom

In this paper we consider the problem of detecting statistically significant sequential patterns in multi-neuronal spike trains. These patterns are characterized by ordered sequences of spikes from different neurons with specific delays…

Neurons and Cognition · Quantitative Biology 2008-08-28 P. S. Sastry , K. P. Unnikrishnan

Linearizing the Heisenberg equations of motion around the ground state of an interacting quantum many-body system, one gets a time-evolution generator in the positive cone of a real symplectic Lie algebra. The presence of disorder in the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 T. Lueck , H. -J. Sommers , M. R. Zirnbauer

Reciprocity is a second-order correlation that has been recently detected in all real directed networks and shown to have a crucial effect on the dynamical processes taking place on them. However, no current theoretical model generates…

Disordered Systems and Neural Networks · Physics 2007-05-23 Diego Garlaschelli , Maria I. Loffredo

This paper presents a significant advancement in the estimation of the Composite Link Model within a penalized likelihood framework, specifically designed to address indirect observations of grouped count data. While the model is effective…

Methodology · Statistics 2025-12-16 Carlo G. Camarda , María Durbán

Analysis of correlation of multiplicities between various rapidity bins is carried out in the framework of a superposition approach consisting of three phases of the ultra-relativistic nuclear collision: early partonic phase, intermediate…

Nuclear Theory · Physics 2015-09-02 Adam Olszewski , Wojciech Broniowski

We propose to describe correlations in classical and quantum systems in terms of full counting statistics of a suitably chosen discrete observable. The method is illustrated with two exactly solvable examples: the classical one-dimensional…

Strongly Correlated Electrons · Physics 2013-04-16 Dmitri A. Ivanov , Alexander G. Abanov

As the complexity of production processes increases, the diversity of data types drives the development of network monitoring technology. This paper mainly focuses on an online algorithm to detect serially correlated directed networks…

Applications · Statistics 2021-12-17 Miaomiao Yu , Yuhao Zhou , Fugee Tsung
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