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The theory of matrix models is reviewed from the point of view of its relation to integrable hierarchies. Determinantal formulas, relation to conformal field models and the theory of Generalized Kontsevich model are discussed in some…

High Energy Physics - Theory · Physics 2016-09-06 A. Morozov

Relative realizability toposes satisfy a universal property that involves regular functors to other categories. We use this universal property to define what relative realizability categories are, when based on other categories than of the…

Logic · Mathematics 2013-08-05 Wouter Pieter Stekelenburg

The R-matrix formalism for the construction of integrable systems with infinitely many degrees of freedom is reviewed. Its application to Poisson, noncommutative and loop algebras as well as central extension procedure are presented. The…

Exactly Solvable and Integrable Systems · Physics 2016-02-18 Maciej Blaszak , Blazej M. Szablikowski

The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally new mathematics such as the do-calculus is required has been…

Machine Learning · Statistics 2019-10-22 Finnian Lattimore , David Rohde

As an emerging interpretable technique, Generalized Additive Models (GAMs) adopt neural networks to individually learn non-linear functions for each feature, which are then combined through a linear model for final predictions. Although…

Machine Learning · Computer Science 2024-08-01 Viet Duong , Qiong Wu , Zhengyi Zhou , Hongjue Zhao , Chenxiang Luo , Eric Zavesky , Huaxiu Yao , Huajie Shao

We present three examples of \textit{multi-topological} semantics for intuitionistic modal logic with one modal operator $\Box$ (which behaves in some sense like necessity). We show that it is possible to treat neighborhood models,…

Logic · Mathematics 2019-03-19 Tomasz Witczak

Recent advances in Bayesian probability theory and its application to cognitive science in combination with the development of a new generation of computational tools and methods for probabilistic computation have led to a 'probabilistic…

Computation and Language · Computer Science 2025-09-29 Christoph Unger , Hendrik Buschmeier

The ability to predict the future in a given domain can be acquired by discovering empirically from experience certain temporal patterns that tend to repeat unerringly. Previous works in time series analysis allow one to make quantitative…

Artificial Intelligence · Computer Science 2013-04-12 Kaihu Chen

This is a largely expository paper about how groups arise or are of interest in model theory. Included are the following topics: classifying groups definable in specific structures or theories and the relation to algebraic groups, groups…

Logic · Mathematics 2021-09-10 Anand Pillay

We show explicitly how the T model, E model, and Hilltop inflations are obtained from the general scalar-tensor theory of gravity with arbitrary conformal factors in the strong coupling limit. We argue that $\xi$ attractors can give any…

General Relativity and Quantum Cosmology · Physics 2016-12-07 Zhu Yi , Yungui Gong

In a recent work we have shown how to construct an information algebra of coherent sets of gambles defined on general possibility spaces. Here we analyze the connection of such an algebra with the set algebra of subsets of the possibility…

Logic in Computer Science · Computer Science 2021-05-28 Juerg Kohlas , Arianna Casanova , Marco Zaffalon

Zonotopal algebra interweaves algebraic, geometric and combinatorial properties of a given linear map X. Of basic significance in this theory is the fact that the algebraic structures are derived from the geometry (via a non-linear…

Commutative Algebra · Mathematics 2012-02-21 Olga Holtz , Amos Ron , Zhiqiang Xu

A growing number of empirical models exhibit set-valued predictions. This paper develops a tractable inference method with finite-sample validity for such models. The proposed procedure uses a robust version of the universal inference…

Econometrics · Economics 2025-01-31 Hiroaki Kaido , Yi Zhang

We present an interpretable companion model for any pre-trained black-box classifiers. The idea is that for any input, a user can decide to either receive a prediction from the black-box model, with high accuracy but no explanations, or…

Machine Learning · Statistics 2020-02-12 Danqing Pan , Tong Wang , Satoshi Hara

The paper uses the formalism of indexed categories to recover the proof of a standard final coalgebra theorem, thus showing existence of final coalgebras for a special class of functors on categories with finite limits and colimits. As an…

Logic · Mathematics 2007-05-23 Benno van den Berg , Federico De Marchi

A lemma of Tits establishes a connection between the simple connectivity of an incidence geometry and the universal completion of an amalgam induced by a sufficiently transitive group of automorphisms of that geometry. In the present paper,…

Geometric Topology · Mathematics 2011-08-18 Ralf Köhl , Hendrik Van Maldeghem

We define a class of higher inductive types that can be constructed in the category of sets under the assumptions of Zermelo-Fraenkel set theory without the axiom of choice or the existence of uncountable regular cardinals. This class…

Logic · Mathematics 2022-02-07 Andrew Swan

Let V be a set of number-theoretical functions. We define a notion of V -realizability for predicate formulas in such a way that the indices of functions in V are used for interpreting the implication and the universal quantifier. In this…

Logic · Mathematics 2022-05-18 Aleksandr Yu. Konovalov

Errors in implicative theories coming from binary data are studied. First, two classes of errors that may affect implicative theories are singled out. Two approaches for finding errors of these classes are proposed, both of them based on…

Artificial Intelligence · Computer Science 2014-10-21 Sergei O. Kuznetsov , Artem Revenko

We propose a new modeling approach that is a generalization of generative and discriminative models. The core idea is to use an implicit parameterization of a joint probability distribution by specifying only the conditional distributions.…

Machine Learning · Computer Science 2016-12-06 Dmitrij Schlesinger , Carsten Rother