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The growing complexity of modern practical problems puts high demands on the mathematical modelling. Given that various models can be used for modelling one physical phenomenon, the role of model comparison and model choice becomes…

Category Theory · Mathematics 2021-08-16 Dmitrii Legatiuk

Modern AI systems are being deployed in complex domains such as medicine, science, and law, where it is important that they not only produce correct answers, but also represent and update uncertain beliefs about the world as new evidence…

Machine Learning · Computer Science 2026-05-28 Chacha Chen , Matthew Jörke , Adam Goliński , Masha Fedzechkina , Guillermo Sapiro , Sinead Williamson , Nicholas Foti

In this paper, an application of automated theorem proving techniques to computational semantics is considered. In order to compute the presuppositions of a natural language discourse, several inference tasks arise. Instead of treating…

Computation and Language · Computer Science 2007-05-23 Christof Monz

Counterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may be analytically…

Machine Learning · Statistics 2024-07-03 Juha Karvanen , Santtu Tikka , Matti Vihola

The classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then it is placed into the framework of evidence theory. Several authors like Laskey, Lehner (1989) and Provan (1990) already…

Artificial Intelligence · Computer Science 2013-03-08 Jurg Kohlas , Paul-Andre Monney

Counterfactual analysis is intuitively performed by humans on a daily basis eg. "What should I have done differently to get the loan approved?". Such counterfactual questions also steer the formulation of scientific hypotheses. More…

Machine Learning · Computer Science 2023-09-18 Juliane Weilbach , Sebastian Gerwinn , Melih Kandemir , Martin Fraenzle

We study the correspondence between Bayesian Networks and graphical representation of proofs in linear logic. The goal of this paper is threefold: to develop a proof-theoretical account of Bayesian inference (in the spirit of the…

Logic in Computer Science · Computer Science 2026-02-05 Rémi Di Guardia , Thomas Ehrhard , Jérôme Evrard , Claudia Faggian

We formulate argumentative relation classification (support vs. attack) as a text-plausibility ranking task. To this aim, we propose a simple reconstruction trick which enables us to build minimal pairs of plausible and implausible texts by…

Computation and Language · Computer Science 2019-09-20 Juri Opitz

An assurance case is intended to provide justifiable confidence in the truth of its top claim, which typically concerns safety or security. A natural question is then "how much" confidence does the case provide? We argue that confidence…

Artificial Intelligence · Computer Science 2024-05-06 Robin Bloomfield , John Rushby

Logical bilateralism challenges traditional concepts of logic by treating assertion and denial as independent yet opposed acts. While initially devised to justify classical logic, its constructive variants show that both acts admit…

Logic in Computer Science · Computer Science 2026-05-05 Victor Barroso-Nascimento , Maria Osório , Elaine Pimentel

Entropy is a measure of heterogeneity widely used in applied sciences, often when data are collected over space. Recently, a number of approaches has been proposed to include spatial information in entropy. The aim of entropy is to…

Statistics Theory · Mathematics 2019-11-12 Linda Altieri , Daniela Cocchi , Giulia Roli

There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewer distinctions. Unfortunately, the level of a Bayesian network…

Artificial Intelligence · Computer Science 2013-02-01 David L. Poole

Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity, with only a limited…

Artificial Intelligence · Computer Science 2023-11-15 Lucas Rizzo , Luca Longo

The learning of mathematics starts early but remains far from any theoretical considerations: pupils' mathematical knowledge is first rooted in pragmatic evidence or conforms to procedures taught. However, learners develop a knowledge which…

History and Overview · Mathematics 2014-03-28 Nicolas Balacheff

Complex phenomena in engineering and the sciences are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood does not exist. In these cases, it is sometimes necessary to estimate an…

Methodology · Statistics 2020-06-18 Niccolò Dalmasso , Ann B. Lee , Rafael Izbicki , Taylor Pospisil , Ilmun Kim , Chieh-An Lin

Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion…

Databases · Computer Science 2011-03-25 José L. Balcázar

The issue of whether nonlinear normalized citation counts can be added is critically important in scientometrics because it touches upon the theoretical foundation of underlying computation in the field. In this paper, we provide rigorous…

Digital Libraries · Computer Science 2025-08-21 Xing Wang , Zhihui Zhang

One advantage of paraconsistent logic is that it can deal with inconsistencies without making the system trivial. However, unlike classical propositional calculus, its deductive system is limited, and the meaning of paraconsistent negation…

Logic · Mathematics 2025-10-14 Oscar Ramírez

A new elementary proof of the prime number theorem presented recently in the framework of a scale invariant extension of the ordinary analysis is re-examined and clarified further. Both the formalism and proof are presented in a much more…

General Mathematics · Mathematics 2011-04-01 Dhurjati Prasad Datta

I discuss the design of the method of entropic inference as a general framework for reasoning under conditions of uncertainty. The main contribution of this discussion is to emphasize the pragmatic elements in the derivation. More…

History and Philosophy of Physics · Physics 2014-12-19 Ariel Caticha
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