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In recent years, the hope to confirm the existence of dark matter by experimentally detecting it has diminished significantly. After more than 30 years of experimental searches, many of the most promising candidates have since been ruled…

History and Philosophy of Physics · Physics 2024-12-19 Simon Allzén

A considerable body of work in AI has been concerned with aggregating measures of confirmatory and disconfirmatory evidence for a common set of propositions. Claiming classical probability to be inadequate or inappropriate, several…

Artificial Intelligence · Computer Science 2013-04-15 Benjamin N. Grosof

This paper studies implications of the consistency conditions among prior, posteriors, and information sets on introspective properties of qualitative belief induced from information sets. The main result reformulates the consistency…

Computer Science and Game Theory · Computer Science 2019-07-23 Satoshi Fukuda

A new contextualised reading of Fritz Zwicky's 1933 article ''The redshift of extragalactic nebulae'' about the virial analysis of the velocity dispersion of galaxies in the Coma cluster leads to a reconsideration of the traditional…

History and Philosophy of Physics · Physics 2026-02-24 Simon Beyne , Christian Marinoni

Trustworthy ML systems should not only return accurate predictions, but also a reliable representation of their uncertainty. Bayesian methods are commonly used to quantify both aleatoric and epistemic uncertainty, but alternative…

Artificial Intelligence · Computer Science 2024-09-11 Mira Jürgens , Nis Meinert , Viktor Bengs , Eyke Hüllermeier , Willem Waegeman

In our previous arXiv papers (more systematically the informational conception is presented in the paper "The Information as Absolute", 2010) it was rigorously shown that Matter in our Universe - and Universe as a whole - are some…

General Physics · Physics 2011-05-05 S. V. Shevchenko , V. V. Tokarevsky

Bayesian inference is often utilized for uncertainty quantification tasks. A recent analysis by Xu and Raginsky 2022 rigorously decomposed the predictive uncertainty in Bayesian inference into two uncertainties, called aleatoric and…

Machine Learning · Statistics 2023-07-25 Futoshi Futami , Tomoharu Iwata

A central challenge in statistical inference is the presence of confounding variables that may distort observed associations between treatment and outcome. Conventional "causal" methods, grounded in assumptions such as ignorability, exclude…

Methodology · Statistics 2025-09-09 Ellis Scharfenaker , Duncan K. Foley

A principle is modified that underlies the theory of organic fiducial inference as this theory was presented in an earlier paper. This modification, which is arguably a natural one to make, allows Bayesian inference to sometimes have a…

Other Statistics · Statistics 2021-11-18 Russell J. Bowater

Turing's (1936) paper on computable numbers has played its role in underpinning different perspectives on the world of information. On the one hand, it encourages a digital ontology, with a perceived flatness of computational structure…

Logic · Mathematics 2015-06-23 S. Barry Cooper

Bayesian analyses are often performed using so-called noninformative priors, with a view to achieving objective inference about unknown parameters on which available data depends. Noninformative priors depend on the relationship of the data…

Methodology · Statistics 2013-08-14 Nicholas Lewis

Because there are similarities between the evaluation of alternative stories in criminal trials and the evaluation of scientific theories, scholars have looked to literature in epistemology and the philosophy of science for insights on the…

Applications · Statistics 2025-01-22 Julia Mortera , William C. Thompson

Epistemic uncertainty arises in lack of complete knowledge about the state of a system. There are multiple mathematical frameworks for measuring such uncertainty quantitatively, often referred to as imprecise probability theories. Inspired…

Category Theory · Mathematics 2026-03-05 Torgeir Aambø

In our previous arXiv papers ("The Information and the Matter", v1, v5; more systematically the informational conception is presented in the paper "The Information as Absolute", 2010) it was rigorously shown that Matter in our Universe -…

General Physics · Physics 2021-09-08 Sergey V. Shevchenko , Vladimir V. Tokarevsky

In a recent paper (arXiv:1106.4546), we introduced "dynamical dark matter," a new framework for dark-matter physics, and outlined its underlying theoretical principles and phenomenological possibilities. Unlike most traditional approaches…

High Energy Physics - Phenomenology · Physics 2013-05-30 Keith R. Dienes , Brooks Thomas

This paper has two purposes. One is to demonstrate contextuality analysis of systems of epistemic random variables. The other is to evaluate the performance of a new, hierarchical version of the measure of (non)contextuality introduced in…

Neurons and Cognition · Quantitative Biology 2020-09-04 Víctor H. Cervantes , Ehtibar N. Dzhafarov

The non-Keplerian galactic rotational curves and the gravitational lensing data strongly indicate a significant dark matter component in the universe. Moreover, these data can be combined to deduce the equation of state of dark matter. Yet,…

Astrophysics · Physics 2007-05-23 D. V. Ahluwalia-Khalilova

The evidence for the existence of dark matter in the universe is reviewed. A general picture emerges, where both baryonic and non-baryonic dark matter is needed to explain current observations. In particular, a wealth of observational…

High Energy Physics - Phenomenology · Physics 2009-07-09 L. Bergstrom

The question of how irreversibility can emerge as a generic phenomena when the underlying mechanical theory is reversible has been a long-standing fundamental problem for both classical and quantum mechanics. We describe a mechanism for the…

Quantum Physics · Physics 2013-09-20 Cozmin Ududec , Nathan Wiebe , Joseph Emerson

Dempster's rule is a fundamental tool for combining belief functions from distinct and reliable sources. However, its intersection-based semantics imposes strong structural restrictions, which limits its flexibility in handling complex…

Artificial Intelligence · Computer Science 2026-05-19 Qianli Zhou , Ye Cui , Zhen Li , Witold Pedrycz , Yong Deng
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