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Related papers: A non-commutative Bayes' theorem

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Bayes' rule tells us how to invert a causal process in order to update our beliefs in light of new evidence. If the process is believed to have a complex compositional structure, we may observe that the inversion of the whole can be…

Category Theory · Mathematics 2023-07-21 Dylan Braithwaite , Jules Hedges , Toby St Clere Smithe

The natural habitat of most Bayesian methods is data represented by exchangeable sequences of observations, for which de Finetti's theorem provides the theoretical foundation. Dirichlet process clustering, Gaussian process regression, and…

Statistics Theory · Mathematics 2015-02-16 Peter Orbanz , Daniel M. Roy

This paper studies the role played by identification in the Bayesian analysis of statistical and econometric models. First, for unidentified models we demonstrate that there are situations where the introduction of a non-degenerate prior…

Econometrics · Economics 2021-10-20 Jean-Pierre Florens , Anna Simoni

We construct uncountably many mutually nonisomorphic simple separable stably finite unital exact C$^\ast$-algebras which are not isomorphic to their opposite algebras. In particular, we prove that there are uncountably many possibilities…

Operator Algebras · Mathematics 2024-02-14 N. Christopher Phillips , Maria Grazia Viola

We introduce enumerative invariants $F_{g,n}$ $(g\geq0$, $n \geq 1)$ associated to a cyclic $A_\infty$ algebra and a splitting of its non-commutative Hodge filtration. These invariants are defined by explicitly computable Feynman sums, and…

Algebraic Geometry · Mathematics 2024-04-03 Andrei Caldararu , Junwu Tu

We introduce the concept of quasi-inverse of quantum and classical channels, prove general properties of these inverses and determine them for a large class of channels acting in an arbitrary finite dimension. Therefore we extend the…

Quantum Physics · Physics 2021-08-11 Fereshte Shahbeigi , Koorosh Sadri , Morteza Moradi , Karol Życzkowski , Vahid Karimipour

The Bayesian statistical paradigm uses the language of probability to express uncertainty about the phenomena that generate observed data. Probability distributions thus characterize Bayesian analysis, with the rules of probability used to…

Computation · Statistics 2020-12-08 Gael M. Martin , David T. Frazier , Christian P. Robert

In this article we provide a substantial discussion on the statistical concept of conditional independence, which is not routinely mentioned in most elementary statistics and mathematical statistics textbooks. Under the assumption of…

Other Statistics · Statistics 2020-03-10 Jun Hu , Xianggui Qu

Using the Baum-Connes conjecture with coefficients, we develop a K-theory formula for reduced C*-algebras of strongly $0$-$E$-unitary inverse semigroups, or equivalently, for certain reduced partial crossed products. In the case of…

Operator Algebras · Mathematics 2021-09-15 Xin Li

We construct a $P(\phi)_2$ Gibbs state on infinite volume periodic surfaces (namely, with discrete ``time translations'') by analogy with 1-dimensional spin chains and establish the mass gap for our Gibbs state, there are no phase…

Mathematical Physics · Physics 2024-08-06 Jiasheng Lin

Essential properties of semiclassical approximation for quantum mechanics are viewed as axioms of an abstract semiclassical mechanics. Its symmetry properties are discussed. Semiclassical systems being invariant under Lie groups are…

Mathematical Physics · Physics 2009-11-07 Oleg Yu. Shvedov

We discuss the use of empirical Bayes for data integration, in the sense of transfer learning. Our main interest is in settings where one wishes to learn structure (e.g. feature selection) and one only has access to incomplete data from…

Methodology · Statistics 2026-02-06 Paul Rognon-Vael , David Rossell

The Bayesian evidence is a key tool in model selection, allowing a comparison of models with different numbers of parameters. Its use in analysis of cosmological models has been limited by difficulties in calculating it, with current…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-01 Juan Garcia-Bellido

Comparison of statistical models (experiments) is an important branch of mathematical statistics, which gives deep insights in many aspects of foundation of statistics. So far, there are two quantum versions of the concept: Comparison with…

Quantum Physics · Physics 2014-09-22 Keiji Matsumoto

Noncommutative lattices have been recently used as finite topological approximations in quantum physical models. As a first step in the construction of bundles and characteristic classes over such noncommutative spaces, we shall study their…

q-alg · Mathematics 2008-02-03 Elisa Ercolessi , Giovanni Landi , Paulo Teotonio-Sobrinho

It is shown how nonlinear versions of quantum mechanics can be refolmulated in terms of a (linear) C*-algebraic theory. Then also their symmetries are described as automorphisms of the correspondong C*-algebra. The requirement of…

Quantum Physics · Physics 2012-12-11 Pavel Bona

In this paper, we introduce a novel generalization of the classical property of algebras known as "being alternative," which we term "partially alternative." This new concept broadens the scope of alternative algebras, offering a fresh…

Rings and Algebras · Mathematics 2025-05-14 Tianran Hua , Ekaterina Napedenina , Marina Tvalavadze

We analyze bipartite matrices and linear maps between matrix algebras, which are respectively, invariant and covariant, under the diagonal unitary and orthogonal groups' actions. By presenting an expansive list of examples from the…

Quantum Physics · Physics 2021-08-11 Satvik Singh , Ion Nechita

The concept of the {\em half density matrix} is proposed. It unifies the quantum states which are described by density matrices and physical processes which are described by completely positive maps. With the help of the half-density-matrix…

Quantum Physics · Physics 2009-11-06 Sixia Yu

Comparing competing mathematical models of complex natural processes is a shared goal among many branches of science. The Bayesian probabilistic framework offers a principled way to perform model comparison and extract useful metrics for…