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Understanding how neural population responses represent sensory information is a central problem in systems neuroscience. One approach is to define a representational geometry on stimulus space in which distances reflect how reliably…

Neurons and Cognition · Quantitative Biology 2026-05-08 Simone Azeglio , Steeve Laquitaine , Ulisse Ferrari , Matthew Chalk

Monte Carlo simulations are powerful tools for understanding the effects of radiation interactions within detector devices allowing not only to evaluate typical estimates for experimental measurements and to serve as means for designing…

Instrumentation and Detectors · Physics 2016-02-09 F. Marinho , K. Akiba

An information measure based on fractional partitions of a set is used to derive a general dependence balance inequality for communication. This inequality is used to obtain new upper bounds on reliable and secret rates for multiterminal…

Information Theory · Computer Science 2026-04-14 Amin Gohari , Gerhard Kramer

Bases, mappings, projections and metrics, natural for Neural network training, are introduced. Graph-theoretical interpretation is offered. Non-Gaussianity naturally emerges, even in relatively simple datasets. Training statistics,…

Computer Vision and Pattern Recognition · Computer Science 2018-09-19 Galin Georgiev

In this paper, we investigate the problem of assessing statistical methods and effectively summarizing results from simulations. Specifically, we consider problems of the type where multiple methods are compared on a reasonably large test…

Applications · Statistics 2015-10-07 Abigail Arnold , Jason Loeppky

To date, testing interactions in high dimensions has been a challenging task. Existing methods often have issues with sensitivity to modeling assumptions and heavily asymptotic nominal p-values. To help alleviate these issues, we propose a…

Machine Learning · Statistics 2012-06-29 Noah Simon , Robert Tibshirani

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The estimation of the parameters of the MLP can be done by maximizing the likelihood of the model. In this framework, it is…

Statistics Theory · Mathematics 2008-02-22 Joseph Rynkiewicz

Mutual information is fundamentally important for measuring statistical dependence between variables and for quantifying information transfer by signaling and communication mechanisms. It can, however, be challenging to evaluate for…

Information Theory · Computer Science 2014-07-29 Clive G. Bowsher , Margaritis Voliotis

A formula is derived for the capacity of the Gaussian channel with a benevolent message-cognizant rate-limited helper that provides a noncausal description of the noise to the encoder and decoder. This capacity is strictly larger than when…

Information Theory · Computer Science 2023-10-25 Amos Lapidoth , Ligong Wang , Yiming Yan

In response to LIGO's observation of GW170104, we performed a series of full numerical simulations of binary black holes, each designed to replicate likely realizations of its dynamics and radiation. These simulations have been performed at…

The mutual information between two jointly distributed random variables $X$ and $Y$ is a functional of the joint distribution $P_{XY},$ which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of…

Information Theory · Computer Science 2016-11-17 Yanjun Han , Or Ordentlich , Ofer Shayevitz

To maximize the accuracy of background simulation and event reconstruction, high-energy neutrino telescopes require detailed knowledge of light propagation over a large volume of detection medium. If light scattering and absorption leng ths…

Computational Physics · Physics 2007-05-23 Predrag Miocinovic , Peter Niessen

The research work outlined in the present note highlights the essential role played by the simulation procedures implemented by us on CINECA supercomputers to complement the mathematical investigations carried within our group over the past…

Statistics Theory · Mathematics 2007-06-13 Elvira Di Nardo , Amelia G. Nobile , Enrica Pirozzi , Luigi M. Ricciardi

In the present paper we are concerned with a numerical algorithm for the approximation of the two-dimensional neural field equation with delay. We consider three numerical examples that have been analysed before by other authors and are…

Numerical Analysis · Mathematics 2015-11-04 Pedro M. Lima , Evelyn Buckwar

It has been proposed that populations of neurons process information in terms of probability density functions (PDFs) of analog variables. Such analog variables range, for example, from target luminance and depth on the sensory interface to…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. J. Barber , J. W. Clark , C. H. Anderson

In particle-based algorithms, the effect of binary collisions is commonly described in a statistical way, using Monte Carlo techniques. It is shown that, in the relativistic regime, stringent constraints should be considered on the sampling…

Plasma Physics · Physics 2009-11-13 F. Peano , M. Marti , L. O. Silva , G. Coppa

Resampling techniques are widely used in statistical inference and ensemble learning, in which estimators' statistical properties are essential. However, existing methods are computationally demanding, because repetitions of…

Machine Learning · Statistics 2019-05-24 Takashi Takahashi , Yoshiyuki Kabashima

Using molecular simulation to aid in the analysis of neutron reflectometry measurements is commonplace. However, reflectometry is a tool to probe large-scale structures, and therefore the use of all-atom simulation may be irrelevant. This…

We consider the 2D acoustic system with the Gaussian pulse as the initial data. This case was proposed at the first Workshop on benchmark problems in computational aeroacoustics, and it is commonly used for the verification of numerical…

Numerical Analysis · Mathematics 2024-04-17 Pavel Bakhvalov

We introduce and study the communication complexity of computing the inner product of two vectors, where the input is restricted w.r.t. a norm $N$ on the space $\mathbb{R}^n$. Here, Alice and Bob hold two vectors $v,u$ such that $\|v\|_N\le…

Computational Complexity · Computer Science 2022-11-28 Alexandr Andoni , Jarosław Błasiok , Arnold Filtser