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The ability to calculate precise likelihood ratios is fundamental to many STEM areas, such as decision-making theory, biomedical science, and engineering. However, there is no assumption-free statistical methodology to achieve this. For…

Statistics Theory · Mathematics 2018-06-19 Rachael L. Bond , Yang-Hui He , Thomas C. Ormerod

Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences…

Quantum Physics · Physics 2009-11-13 Matthew Leifer , David Poulin

I show that probabilities in quantum mechanics are a measure of belief in the presence of human ignorance, just like all other probabilities. The Born interpretation of the square of modulus of the wave function arises from the interaction…

Quantum Physics · Physics 2007-05-23 Frank J. Tipler

We derive an analogue of the quantum total probability rule by constructing a probability theory based on paraconsistent logic. Bayesian probability theory is constructed upon classical logic and a desiderata, that is, a set of desired…

Quantum Physics · Physics 2014-08-25 R. Salazar , C. Jara-Figueroa , A. Delgado

We introduce a logic modelling some aspects of the behaviour of the measurement process, in such a way that no direct mention of quantum states is made, thus avoiding the problems associated to this rather evasive notion. We then study some…

Quantum Physics · Physics 2015-11-06 Olivier Brunet

Quantum mechanics can emerge from classical statistics. A typical quantum system describes an isolated subsystem of a classical statistical ensemble with infinitely many classical states. The state of this subsystem can be characterized by…

Quantum Physics · Physics 2015-05-13 C. Wetterich

The Bayesian approach to quantum mechanics of Caves, Fuchs and Schack is presented. Its conjunction of realism about physics along with anti-realism about much of the structure of quantum theory is elaborated; and the position defended from…

Quantum Physics · Physics 2008-04-15 Christopher G. Timpson

Quantum state tomography, an important task in quantum information processing, aims at reconstructing a state from prepared measurement data. Bayesian methods are recognized to be one of the good and reliable choice in estimating quantum…

Statistics Theory · Mathematics 2017-06-15 The Tien Mai , Pierre Alquier

The notion of context (complex of physical conditions) is basic in this paper. We show that the main structures of quantum theory (interference of probabilities, Born's rule, complex probabilistic amplitudes, Hilbert state space,…

Quantum Physics · Physics 2009-11-10 Andrei Khrennikov

This paper presents a minimal formulation of nonrelativistic quantum mechanics, by which is meant a formulation which describes the theory in a succinct, self-contained, clear, unambiguous and of course correct manner. The bulk of the…

History and Philosophy of Physics · Physics 2018-04-04 R. Friedberg , P. C. Hohenberg

A Bayesian approach is developed to determine quantum mechanical potentials from empirical data. Bayesian methods, combining empirical measurements and "a priori" information, provide flexible tools for such empirical learning problems. The…

Quantum Physics · Physics 2009-11-06 J. C. Lemm , J. Uhlig

Implementing Bayesian inference is often computationally challenging in applications involving complex models, and sometimes calculating the likelihood itself is difficult. Synthetic likelihood is one approach for carrying out inference…

Computation · Statistics 2021-03-15 David T. Frazier , David J. Nott , Christopher Drovandi , Robert Kohn

According to the probability ranking principle, the document set with the highest values of probability of relevance optimizes information retrieval effectiveness given the probabilities are estimated as accurately as possible. The key…

Information Retrieval · Computer Science 2011-08-30 Massimo Melucci

We constructed a Hilbert space representation of a contextual Kolmogorov model. This representation is based on two fundamental observables -- in the standard quantum model these are position and momentum observables. This representation…

Quantum Physics · Physics 2015-06-26 Andrei Khrennikov

Quantum algorithms profit from the interference of quantum states in an exponentially large Hilbert space and the fact that unitary transformations on that Hilbert space can be broken down to universal gates that act only on one or two…

Quantum Physics · Physics 2022-03-14 Daniel Braun , Ronny Müller

In statistical practice, a realistic Bayesian model for a given data set can be defined by a likelihood function that is analytically or computationally intractable, due to large data sample size, high parameter dimensionality, or complex…

Methodology · Statistics 2019-03-19 George Karabatsos , Fabrizio Leisen

We present a comparative study between classical probability and quantum probability from the Bayesian viewpoint, where probability is construed as our rational degree of belief on whether a given statement is true. From this viewpoint,…

Quantum Physics · Physics 2025-05-05 Tsubasa Ichikawa

According to the subjective Bayesian interpretation of quantum theory (QBism), quantum mechanics is a tool that an agent would be wise to use when making bets about natural phenomena. In particular, the Born rule is understood to be a…

Quantum computation has suggested new forms of quantum logic, called quantum computational logics. The basic semantic idea is the following: the meaning of a sentence is identified with a quregister, a system of qubits, representing a…

Quantum Physics · Physics 2007-05-23 M. L. Dalla Chiara , R. Giuntini , R. Leporini

We develop a systematic approach to quantum probability as a theory of rational betting in quantum gambles. In these games of chance the agent is betting in advance on the outcomes of several (finitely many) incompatible measurements. One…

Quantum Physics · Physics 2007-05-23 I. Pitowsky
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