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We describe a Groebner basis of relations among conditional probabilities in a discrete probability space, with any set of conditioned-upon events. They may be specialized to the partially-observed random variable case, the purely…

Probability · Mathematics 2008-08-11 Jason Morton

The Poisson probability distribution is frequently encountered in physical science measurements. In spite of the simplicity and familiarity of this distribution, there is considerable confusion among physicists concerning the description of…

Data Analysis, Statistics and Probability · Physics 2026-04-22 Frank C. Porter

We consider a setting where an agent's uncertainty is represented by a set of probability measures, rather than a single measure. Measure-bymeasure updating of such a set of measures upon acquiring new information is well-known to suffer…

Computer Science and Game Theory · Computer Science 2013-02-26 Joseph Y. Halpern , Samantha Leung

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

In this paper, we derive a representation for the value process associated to the solutions of FBSDEs in a jump-diffusion setting under multiple probability measures. Motivated by concrete financial problems, the latter representations are…

Probability · Mathematics 2022-07-13 Luca Di Persio , Alessandro Gnoatto , Marco Patacca

The new interpretation of Quantum Mechanics is based on a complex probability theory. An interpretation postulate specifies events which can be observed and it follows that the complex probability of such event is, in fact, a real positive…

Quantum Physics · Physics 2007-05-23 Jiri Soucek

We propose flexible Gaussian representations for conditional cumulative distribution functions and give a concave likelihood criterion for their estimation. Optimal representations satisfy the monotonicity property of conditional cumulative…

Econometrics · Economics 2025-04-22 Richard Spady , Sami Stouli

In the interpretation of experimental data, one is actually looking for plausible explanations. We look for a measure of plausibility, with which we can compare different possible explanations, and which can be combined when there are…

Artificial Intelligence · Computer Science 2010-12-30 Wan Ahmad Tajuddin Wan Abdullah

In this paper we study generalised Ising Glauber models with inflow of informa- tion in one dimension and derive expressions for the exit probability using well established analytical methods. The analytical expressions agree very well with…

Statistical Mechanics · Physics 2016-02-11 Parna Roy , Parongama Sen

We introduced a new continued fraction expansions in our previous paper. For these expansions, we show formulae of probability about incomplete quotients. Furthermore, we prove the existence of invariant measures with respect to the…

Number Theory · Mathematics 2010-11-24 Dan Lascu , Katsunori Kawamura

In the framework of Gibbs statistical theory, the issue of the distribution of particle sizes forming the statistical system and the moments of this distribution are considered. This task is relevant for a wide variety of applications. The…

Statistical Mechanics · Physics 2019-10-14 V. V. Ryazanov

Sensitivity properties describe how changes to the input of a program affect the output, typically by upper bounding the distance between the outputs of two runs by a monotone function of the distance between the corresponding inputs. When…

Logic in Computer Science · Computer Science 2020-08-11 Alejandro Aguirre , Gilles Barthe , Justin Hsu , Benjamin Lucien Kaminski , Joost-Pieter Katoen , Christoph Matheja

Deriving exact density functions for Gibbs point processes has been challenging due to their general intractability, stemming from the intractability of their normalising constants/partition functions. This paper offers a solution to this…

Probability · Mathematics 2024-06-12 Ottmar Cronie

As for other latent-variable problems, exact Bayesian analysis is typically not practicable for mixture problems and approximate methods have been developed. Variational Bayes tends to produce approximate posterior distributions for…

Statistics Theory · Mathematics 2026-02-24 Nils Lid Hjort , Mike Titterington

Probability measures by themselves, are known to be inappropriate for modeling the dynamics of plain belief and their excessively strong measurability constraints make them unsuitable for some representational tasks, e.g. in the context of…

Artificial Intelligence · Computer Science 2013-02-28 Emil Weydert

There are considered some corollaries of certain hypotheses on the observation process of microphenomena. We show that an enlargement of the phase space and of its motion group and an account for the diffusion motions of microsystems in the…

Quantum Physics · Physics 2007-05-23 E. M. Beniaminov

A new combinatorial-probabilistic diagnostic entropy has been introduced. It describes the pair-wise sum of probabilities of system conditions that have to be distinguished during the diagnosing process. The proposed measure describes the…

Information Theory · Computer Science 2009-09-29 Henryk Borowczyk

Evidently, some relaxation dynamics, e.g. exponential decays, are much more common in nature than others. Recently there have been attempts to explain this observation on the basis of ``typicality of perturbations'' with respect to their…

Quantum Physics · Physics 2020-04-29 Robin Heveling , Lars Knipschild , Jochen Gemmer

We study representations of a random variable $\xi$ as an integral of an adapted process with respect to the Lebesgue measure. The existence of such representations in two different regularity classes is characterized in terms of the…

Probability · Mathematics 2023-08-08 Sara Biagini , Gordan Zitkovic

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in…

Machine Learning · Computer Science 2013-11-12 Spencer Greenberg , Mehryar Mohri
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