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Related papers: Functional units for natural numbers

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Expanding upon recent work, a new class of $A$-functions is introduced that can be viewed as an appropriate generalization of the class of regular $A$-functions, the class of structured $A$-functions, and the class of perfect $A$-functions.…

Number Theory · Mathematics 2022-03-01 Joseph Burnett , Alex Taylor

In this paper, we study classes of structures and individual structures for which programs implementing functions defined everywhere are equivalent to finite tree-programs. The programs under consideration may have cycles and at most…

Logic in Computer Science · Computer Science 2025-01-06 Mikhail Moshkov

Any function can be constructed using a hierarchy of simpler functions through compositions. Such a hierarchy can be characterized by a binary rooted tree. Each node of this tree is associated with a function which takes as inputs two…

Machine Learning · Computer Science 2019-10-23 Roozbeh Farhoodi , Khashayar Filom , Ilenna Simone Jones , Konrad Paul Kording

We prove that every nonnegative continuous real-valued function on a given compact metric space is the uniform limit of some increasing sequence of nonnegative simple functions being linear combinations of indicators of open sets; here the…

General Mathematics · Mathematics 2020-10-21 Yu-Lin Chou

One of the fundamental results in computability is the existence of well-defined functions that cannot be computed. In this paper we study the effects of data representation on computability; we show that, while for each possible way of…

Computational Complexity · Computer Science 2017-06-30 Jaun Casanova , Simone Santini

Building upon the findings presented in the first three papers of this series, we formulate an effective field theory for interacting collective states. These states consist of a large number of interconnected neurons and are distinguished…

Biological Physics · Physics 2024-05-22 Pierre Gosselin , Aïleen Lotz

The functional derivative of the effective action with respect to an external field is part of the equation of motion of this field if one-loop effects induced by quantum fluctuations or thermal fluctuations are included when minimizing the…

High Energy Physics - Phenomenology · Physics 2016-09-01 J. Baacke , A. Suerig

We consider the task of computing functions $f: \mathbb{N}^k\to \mathbb{N}$, where $ \mathbb{N}$ is the set of natural numbers, by finite teams of agents modelled as deterministic finite automata. The computation is carried out in a…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-10-03 Debasish Pattanayak , Andrzej Pelc

We introduce a novel approach that exploits the intersection of quantum computing, machine learning and reduced density matrix functional theory to leverage the potential of quantum computing to improve simulations of interacting quantum…

Quantum Physics · Physics 2025-12-16 Martin J. Uttendorfer , Daniel Barragan-Yani , Matthias Sperl , Marc Landmann

The article bridges between two major paradigms in computation, the functional, at basis computation from input to output, and the interactive, where computation reacts to its environment while underway. Central to any compositional theory…

Programming Languages · Computer Science 2023-04-11 Glynn Winskel

The universal approximation theorem is generalised to uniform convergence on the (noncompact) input space $\mathbb{R}^n$. All continuous functions that vanish at infinity can be uniformly approximated by neural networks with one hidden…

Machine Learning · Computer Science 2024-03-05 Teun D. H. van Nuland

We describe a new logical data model, called the concept-oriented model (COM). It uses mathematical functions as first-class constructs for data representation and data processing as opposed to using exclusively sets in conventional…

Databases · Computer Science 2019-11-19 Alexandr Savinov

We introduce an algebraic framework for interacting quantum systems that enables studying complex phenomena, characterized by the coexistence and competition of various broken symmetry states of matter. The approach unveils the hidden unity…

Strongly Correlated Electrons · Physics 2009-11-07 G. Ortiz , C. D. Batista

This paper initiates a systematic study of quantum functions, which are (partial) functions defined in terms of quantum mechanical computations. Of all quantum functions, we focus on resource-bounded quantum functions whose inputs are…

Quantum Physics · Physics 2007-05-23 Tomoyuki Yamakami

We discuss various universality aspects of numerical computations using standard algorithms. These aspects include empirical observations and rigorous results. We also make various speculations about computation in a broader sense.

Probability · Mathematics 2017-03-24 Percy Deift , Thomas Trogdon

Structural operational semantics can be studied at the general level of distributive laws of syntax over behaviour. This yields specification formats for well-behaved algebraic operations on final coalgebras, which are a domain for the…

Logic in Computer Science · Computer Science 2012-08-15 Marcello M. Bonsangue , Stefan Milius , Jurriaan Rot

Cognitive Architectures are the forefront of the research into developing an artificial cognition. However, they approach the problem from a separated memory and program model of computation. This model of computation poses a fundamental…

Artificial Intelligence · Computer Science 2024-11-07 Alfredo Ibias , Hector Antona , Guillem Ramirez-Miranda , Enric Guinovart , Eduard Alarcon

We prove a number of results motivated by global questions of uniformity in computability theory, and universality of countable Borel equivalence relations. Our main technical tool is a game for constructing functions on free products of…

Logic · Mathematics 2020-01-20 Andrew S Marks

A central question in cognitive science is whether conceptual representations converge onto a shared manifold to support generalization, or diverge into orthogonal subspaces to minimize task interference. While prior work has discovered…

Computation and Language · Computer Science 2026-02-09 Zhimin Hu , Lanhao Niu , Sashank Varma

The output of a machine learning algorithm can usually be represented by one or more multivariate functions of its input variables. Knowing the global properties of such functions can help in understanding the system that produced the data…

Machine Learning · Statistics 2024-03-21 Jerome H. Friedman