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Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or…

Machine Learning · Statistics 2014-02-06 Scott W. Linderman , Ryan P. Adams

It is argued that 4-valued paraconsistent truth values (called here "p-bits") can serve as a conceptual, mathematical and practical foundation for highly AI-relevant forms of probabilistic logic and probabilistic programming and concept…

Artificial Intelligence · Computer Science 2021-01-15 Ben Goertzel

The Nonassociative Lambek Calculus (NL) represents a logic devoid of the structural rules of exchange, weakening, and contraction, and it does not presume the associativity of its connectives. Its finitary consequence relation is decidable…

Logic in Computer Science · Computer Science 2025-01-03 Paweł Płaczek

In aggregated variables the impact of interventions is typically ill-defined because different micro-realizations of the same macro-intervention can result in different changes of downstream macro-variables. We show that this…

Artificial Intelligence · Computer Science 2024-02-23 Yuchen Zhu , Kailash Budhathoki , Jonas Kuebler , Dominik Janzing

Modelling complex information systems often entails the need for dealing with scenarios of inconsistency in which several requirements either reinforce or contradict each other. In this kind of scenarios, arising e.g. in knowledge…

Logic in Computer Science · Computer Science 2022-04-15 Ana Cruz , Alexandre Madeira , Luís Soares Barbosa

We study various notions of dependency in semiring team semantics. Semiring teams are essentially database relations, where each tuple is annotated with some element from a positive semiring. We consider semiring generalizations of several…

Logic in Computer Science · Computer Science 2025-10-10 Minna Hirvonen

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk…

Theoretical Economics · Economics 2020-08-11 Christian Tarsney

Probabilistic circuits compute multilinear polynomials that represent multivariate probability distributions. They are tractable models that support efficient marginal inference. However, various polynomial semantics have been considered in…

Artificial Intelligence · Computer Science 2024-08-09 Oliver Broadrick , Honghua Zhang , Guy Van den Broeck

The work concentrates on relations, which are general and model independent in chaotic system, between time averages of a few (typically {\it very few}) observables. Equilibrium thermodynamics provides a guide and here is attempted to argue…

Chaotic Dynamics · Physics 2025-06-12 Giovanni Gallavotti

We analyze, from a theoretical viewpoint, the bidirectional interdisciplinary relation between mathematics and psychology, focused on the mathematical theory of deterministic dynamical systems, and in particular, on the theory of chaos. On…

Chaotic Dynamics · Physics 2012-07-23 Eleonora Catsigeras

Between the two dominant schools of thought in statistics, namely, Bayesian and classical/frequentist, a main difference is that the former is grounded in the mathematically rigorous theory of probability while the latter is not. In this…

Statistics Theory · Mathematics 2021-12-22 Ryan Martin

The probabilistic satisfiability of a logical expression is a fundamental concept known as the partition function in statistical physics and field theory, an evaluation of a related graph's Tutte polynomial in mathematics, and the…

Discrete Mathematics · Computer Science 2022-06-09 Stephen Eubank , Madhurima Nath , Yihui Ren , Abhijin Adiga

In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of…

Artificial Intelligence · Computer Science 2012-10-19 Giuseppe Sanfilippo

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent, rendering standard approaches…

Econometrics · Economics 2022-06-07 Victor H. Aguiar , Nail Kashaev , Roy Allen

In this paper, we consider sequences of polynomials that satisfy differential--difference recurrences. Our interest is motivated by the fact that polynomials satisfying such recurrences frequently appear as generating polynomials of integer…

Combinatorics · Mathematics 2016-05-11 Pawel Hitczenko , Amanda Lohss

Regression is one of the most fundamental statistical inference problems. A broad definition of regression problems is as estimation of the distribution of an outcome using a family of probability models indexed by covariates. Despite the…

Statistics Theory · Mathematics 2023-09-26 Peter Mueller , Fernando Andrés Quintana , Garritt L. Page

Association Rules are a basic concept of data mining. They are, however, not understood as logical objects which can be used for reasoning. The purpose of this paper is to investigate a model based semantic for implications with certain…

Logic in Computer Science · Computer Science 2012-01-31 Daniel Borchmann

We show that intuitionistic propositional logic is \emph{Carnap categorical}: the only interpretation of the connectives consistent with the intuitionistic consequence relation is the standard interpretation. This holds relative to the most…

Logic · Mathematics 2022-12-27 Haotian Tong , Dag Westerståhl

We view sorites in terms of stimuli acting upon a system and evoking this system's responses. Supervenience of responses on stimuli implies that they either lack tolerance (i.e., they change in every vicinity of some of the stimuli), or…

Artificial Intelligence · Computer Science 2015-04-27 Damir D. Dzhafarov , Ehtibar N. Dzhafarov

Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action…

General Economics · Economics 2022-05-03 Stefan Rass , Sandra König , Stefan Schauer