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Related papers: A general definition of dependent type theories

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A type analysable in one-based types in a simple theory is itself one-based.

Logic · Mathematics 2019-04-15 Frank Olaf Wagner

Contextual type theory distinguishes between bound variables and meta-variables to write potentially incomplete terms in the presence of binders. It has found good use as a framework for concise explanations of higher-order unification,…

Logic in Computer Science · Computer Science 2011-11-02 Mathieu Boespflug , Brigitte Pientka

Homotopy Type Theory is a new field of mathematics based on the surprising and elegant correspondence between Martin-Lofs constructive type theory and abstract homotopy theory. We have a powerful interplay between these disciplines - we can…

Logic in Computer Science · Computer Science 2014-02-10 Kristina Sojakova

The study of homotopy theoretic phenomena in the language of type theory is sometimes loosely called `synthetic homotopy theory'. Homotopy theory in type theory is only one of the many aspects of homotopy type theory, which also includes…

Logic · Mathematics 2019-06-25 Egbert Rijke

We regard explanations as a blending of the input sample and the model's output and offer a few definitions that capture various desired properties of the function that generates these explanations. We study the links between these…

Machine Learning · Computer Science 2020-01-16 Lior Wolf , Tomer Galanti , Tamir Hazan

The main aim of this paper is to establish several Landau-type theorems for certain bounded poly-analytic functions and reduced poly-analytic functions that generalize some previously established results.

Complex Variables · Mathematics 2025-08-28 Vasudevarao Allu , Raju Biswas , Rajib Mandal , Hiroshi Yanagihara

We present an approach to support partiality in type-level computation without compromising expressiveness or type safety. Existing frameworks for type-level computation either require totality or implicitly assume it. For example, type…

Programming Languages · Computer Science 2017-06-30 J. Garrett Morris , Richard Eisenberg

We give a theoretical model of conjunctions $E\wedge F$ and implications $E\implies F$ where $F$ is meaningful only when $E$ is true, a situation which is very often encountered in everyday mathematics, and which was already formalized by…

Logic · Mathematics 2018-05-10 Matthieu Herrmann , Alain Prouté

In this paper I survey the sources of inspiration for my own and co-authored work in trying to develop a general theory of graph polynomials. I concentrate on meta-theorems, i.e., theorem which depend only on the form infinite classes of…

Combinatorics · Mathematics 2024-05-14 Johann A. Makowsky

Empirical process theory for i.i.d. observations has emerged as a ubiquitous tool for understanding the generalization properties of various statistical problems. However, in many applications where the data exhibit temporal dependencies…

Statistics Theory · Mathematics 2024-01-18 Nabarun Deb , Debarghya Mukherjee

The definition is a common form of human expert knowledge, a building block of formal science and mathematics, a foundation for database theory and is supported in various forms in many knowledge representation and formal specification…

Logic in Computer Science · Computer Science 2017-02-16 Marc Denecker , Bart Bogaerts , Joost Vennekens

Type-free systems of logic are designed to consistently handle significant instances of self-reference. Some consistent type-free systems also have the feature of allowing the sort of general abstraction or comprehension principle that…

Logic · Mathematics 2007-05-23 Wayne Aitken , Jeffrey A. Barrett

Formal deductive systems are very common in computer science. They are used to represent logics, programming languages, and security systems. Moreover, writing programs that manipulate them and that reason about them is important and…

Programming Languages · Computer Science 2018-05-21 Francisco Ferreira Ruiz

Representation learning seeks meaningful sensory representations without supervision and can model aspects of human development. Although many neural networks empirically learn useful features, a principled account of what makes a…

Machine Learning · Computer Science 2026-05-07 Takayuki Komatsu , Yoshiyuki Ohmura , Yasuo Kuniyoshi

A general class of models is proposed that is able to estimate the whole predictive distribution of a dependent variable $Y$ given a vector of explanatory variables $\xb$. The models exploit that the strength of explanatory variables to…

Methodology · Statistics 2021-03-25 Gerhard Tutz

The defunctionalization translation that eliminates higher-order functions from programs forms a key part of many compilers. However, defunctionalization for dependently-typed languages has not been formally studied. We present the first…

Programming Languages · Computer Science 2023-04-11 Yulong Huang , Jeremy Yallop

Reynolds' parametricity originally equips types with proof-irrelevant binary propositional relations over the types. But such relations can also be taken proof-relevant or unary, and described either in an indexed or fibred way.…

Logic in Computer Science · Computer Science 2026-02-16 Hugo Herbelin , Ramkumar Ramachandra

Inductive and coinductive types are commonly construed as ontological (Church-style) types, denoting canonical data-sets such as natural numbers, lists, and streams. For various purposes, notably the study of programs in the context of…

Logic in Computer Science · Computer Science 2015-07-01 Daniel M Leivant

How should my own decisions affect my beliefs about the outcomes I expect to achieve? If taking a certain action makes me view myself as a certain type of person, it might affect how I think others view me, and how I view others who are…

Artificial Intelligence · Computer Science 2023-07-21 Matt MacDermott , Tom Everitt , Francesco Belardinelli

Interventional causal models describe several joint distributions over some variables used to describe a system, one for each intervention setting. They provide a formal recipe for how to move between the different joint distributions and…

Machine Learning · Statistics 2021-08-06 Eigil F. Rischel , Sebastian Weichwald
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