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Explainability methods are often challenging to evaluate and compare. With a multitude of explainers available, practitioners must often compare and select explainers based on quantitative evaluation metrics. One particular differentiator…

Machine Learning · Computer Science 2025-03-13 Davin Hill , Josh Bone , Aria Masoomi , Max Torop , Jennifer Dy

Inferring a quantum system from incomplete information is a common problem in many aspects of quantum information science and applications, where the principle of maximum entropy (MaxEnt) plays an important role. The quantum state…

Quantum Physics · Physics 2022-07-26 Shi-Yao Hou , Zipeng Wu , Jinfeng Zeng , Ningping Cao , Chenfeng Cao , Youning Li , Bei Zeng

Investigating a problem posed by W. Hengartner (2000), we study the maximal valence (number of preimages of a prescribed point in the complex plane) of logharmonic polynomials, i.e., complex functions that take the form $f(z) = p(z)…

Complex Variables · Mathematics 2025-03-26 Dmitry Khavinson , Erik Lundberg , Sean Perry

In this paper, we give a frequency interpretation of negative probability, as well as of extended probability, demonstrating that to a great extent, these new types of probabilities, behave as conventional probabilities. Extended…

Data Analysis, Statistics and Probability · Physics 2013-06-10 Mark Burgin

Deep directed generative models have attracted much attention recently due to their expressive representation power and the ability of ancestral sampling. One major difficulty of learning directed models with many latent variables is the…

Machine Learning · Computer Science 2015-06-16 Siqi Nie , Qiang Ji

When the data do not conform to the hypothesis of a known sampling-variance, the fitting of a constant to a set of measured values is a long debated problem. Given the data, fitting would require to find what measurand value is the most…

Data Analysis, Statistics and Probability · Physics 2020-07-21 Giovanni Mana , Enrico Massa , Maria Predescu

In 1910 Einstein published a crucial aspect of his understanding of Boltzmann entropy. He essentially argued that the likelihood function of any system composed by two probabilistically independent subsystems {\it ought} to be factorizable…

Statistical Mechanics · Physics 2015-05-22 Constantino Tsallis , Hans J. Haubold

The multinomial model is one of the simplest statistical models. When constraints are placed on the possible values for the probabilities, however, it becomes much more difficult to deal with. Model checking and checking for prior-data…

Statistics Theory · Mathematics 2018-08-22 Berthold-Georg Englert , Michael Evans , Gun Ho Jang , Hui Khoon Ng , David Nott , Yi-Lin Seah

The word-frequency distribution provides the fundamental building blocks that generate discourse in language. It is well known, from empirical evidence, that the word-frequency distribution of almost any text is described by Zipf's law, at…

Physics and Society · Physics 2020-11-09 Alvaro Corral , Montserrat Garcia del Muro

By representing the range of fair betting odds according to a pair of confidence set estimators, dual probability measures on parameter space called frequentist posteriors secure the coherence of subjective inference without any prior…

Statistics Theory · Mathematics 2012-05-02 David R. Bickel

Max-stable processes provide natural models for the modelling of spatial extreme values observed at a set of spatial sites. Full likelihood inference for max-stable data is, however, complicated by the form of the likelihood function as it…

Methodology · Statistics 2022-12-15 Patrik Andersson , Alexander Engberg

A finite dimensional quantum system for which the quantum chaos conjecture applies has eigenstates, which show the same statistical properties than the column vectors of random orthogonal or unitary matrices. Here, we consider the different…

Mathematical Physics · Physics 2017-10-05 L. Alonso , T. Gorin

The Principle of Insufficient Reason (PIR) assigns equal probabilities to each alternative of a random experiment whenever there is no reason to prefer one over the other. The Maximum Entropy Principle (MaxEnt) generalizes PIR to the case…

Machine Learning · Statistics 2021-11-25 Dominik Janzing

The notion of objective probability or chance, as a physical trait of the world, has proved elusive; the identification of chances with actual frequencies does not succeed. An adequate theory of chance should explain not only the connection…

Quantum Physics · Physics 2016-09-16 Simon Saunders

We show that the quantum-mechanical probability distribution involving complex probability amplitudes can be derived from three natural conditions imposed on a relativistically invariant probability function describing the motion of a…

Quantum Physics · Physics 2025-12-12 Karol Sajnok , Kacper Dębski , Andrzej Dragan

Let $f$ be a Rademacher or a Steinhaus random multiplicative function. Let $\varepsilon>0$ small. We prove that, as $x\rightarrow +\infty$, we almost surely have $$\bigg|\sum_{\substack{n\leq x\\…

Number Theory · Mathematics 2021-05-21 Daniele Mastrostefano

In 1989, Deutsch gave a basic physical explanation of why quantum-mechanical probabilities are squares of amplitudes. Essentially, a general state vector is transformed into a highly symmetric equal-amplitude superposition. The argument was…

Quantum Physics · Physics 2007-05-23 L. Polley

Traditionally, the Method of (Shannon-Kullback's) Relative Entropy Maximization (REM) is considered with linear moment constraints. In this work, the method is studied under frequency moment constraints which are non-linear in…

Data Analysis, Statistics and Probability · Physics 2012-08-27 M. Grendar, , M. Grendar

We describe a particular approach for the construction of a nonequilibrium statistical ensemble formalism for the treatment of dissipative many-body systems. This is the so-called Nonequilibrium Statistical Operator Method, based on the…

Statistical Mechanics · Physics 2016-08-31 R. Luzzi , A. R. Vasconcellos , J. G. Ramos

The frequentist interpretation of measurement results requires the specification of an ensemble of independent replications of the same experiment. For complex calculations of bias, coverage, significance, etc., this ensemble is often…

Data Analysis, Statistics and Probability · Physics 2014-11-18 Luc Demortier
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