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The paper introduces a novel algorithm for computing the output admissible set of linear discrete-time systems subject to input saturation. The proposed method takes advantage of the piecewise-affine dynamics to propagate the output…

Optimization and Control · Mathematics 2023-11-29 Yaashia Gautam , Marco M. Nicotra

We prove that the existence of finite combinatorial objects such as affine planes, mutually orthogonal Latin squares, and resolvable balanced incomplete block designs can be reformulated as the existence of certain algorithmic reductions…

Combinatorics · Mathematics 2026-04-21 Damir D. Dzhafarov , Jun le Goh

Data-driven modeling of spatiotemporal physical processes with general deep learning methods is a highly challenging task. It is further exacerbated by the limited availability of data, leading to poor generalizations in standard neural…

Machine Learning · Computer Science 2021-04-14 Timothy Praditia , Matthias Karlbauer , Sebastian Otte , Sergey Oladyshkin , Martin V. Butz , Wolfgang Nowak

A linear parameter must be consumed exactly once in the body of its function. When declaring resources such as file handles and manually managed memory as linear arguments, a linear type system can verify that these resources are used…

Programming Languages · Computer Science 2022-07-25 Arnaud Spiwack , Csongor Kiss , Jean-Philippe Bernardy , Nicolas Wu , Richard Eisenberg

We introduce the strongly NP-complete pagination problem, an extension of BIN PACKING where packing together two items may make them occupy less volume than the sum of their individual sizes. To achieve this property, an item is defined as…

Data Structures and Algorithms · Computer Science 2017-09-06 Aristide Grange , Imed Kacem , Sébastien Martin

We propose a new interpretation of measures of information and disorder by connecting these concepts to group theory in a new way. Entropy and group theory are connected here by their common relation to sets of permutations. A combinatorial…

Information Theory · Computer Science 2019-11-25 David J. Galas

Why rely on dense neural networks and then blindly sparsify them when prior knowledge about the problem structure is already available? Many inverse problems admit algorithm-unrolled networks that naturally encode physics and sparsity. In…

Machine Learning · Computer Science 2025-10-14 Arian Eamaz , Farhang Yeganegi , Mojtaba Soltanalian

In the paper we present results to develop an irreducible theory of complex systems in terms of self-organization processes of prime integer relations. Based on the integers and controlled by arithmetic only the self-organization processes…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Victor Korotkikh , Galina Korotkikh

An equivalent definition of the Fibonacci numbers is that they are the unique sequence such that every integer can be written uniquely as a sum of non-adjacent terms. We can view this as we have bins of length 1, we can take at most one…

Physics-informed neural networks (PINNs) are capable of finding the solution for a given boundary value problem. We employ several ideas from the finite element method (FEM) to enhance the performance of existing PINNs in engineering…

Computational Engineering, Finance, and Science · Computer Science 2022-10-05 Shahed Rezaei , Ali Harandi , Ahmad Moeineddin , Bai-Xiang Xu , Stefanie Reese

Fair termination is the property of programs that may diverge "in principle" but that terminate "in practice", i.e. under suitable fairness assumptions concerning the resolution of non-deterministic choices. We study a conservative…

Logic in Computer Science · Computer Science 2022-07-11 Luca Ciccone , Luca Padovani

In this paper, we introduce and develop the circle embedding method. This method hinges essentially on a combinatorial-geometric structure which we choose to call circles of partition. We provide applications in the context of problems that…

General Mathematics · Mathematics 2026-04-21 Theophilus Agama , Berndt Gensel

Recently, physics-informed neural networks (PINNs) have offered a powerful new paradigm for solving problems relating to differential equations. Compared to classical numerical methods PINNs have several advantages, for example their…

Computational Physics · Physics 2024-06-21 Ben Moseley , Andrew Markham , Tarje Nissen-Meyer

The main result of this paper is to show that all binomial identities are orderable. This is a natural statement in the combinatorial theory of finite sets, which can also be applied in distributed computing to derive new strong bounds on…

Discrete Mathematics · Computer Science 2016-06-24 Dmitry N. Kozlov

In this work, we study physics-informed neural networks (PINNs) constrained by partial differential equations (PDEs) and their application in approximating PDEs with two characteristic scales. From a continuous perspective, our formulation…

Optimization and Control · Mathematics 2024-09-06 Michael Hintermüller , Denis Korolev

This study presents a discrete physics-informed neural network (dPINN) framework, enhanced with enforced interface constraints (EIC), for modeling physical systems using the domain decomposition method (DDM). Built upon finite element-style…

Computational Engineering, Finance, and Science · Computer Science 2025-05-19 Jichao Yin , Mingxuan Li , Jianguang Fang , Hu Wang

We introduce Physics Informed Symbolic Networks (PISN) which utilize physics-informed loss to obtain a symbolic solution for a system of Partial Differential Equations (PDE). Given a context-free grammar to describe the language of symbolic…

Machine Learning · Computer Science 2022-12-21 Ritam Majumdar , Vishal Jadhav , Anirudh Deodhar , Shirish Karande , Lovekesh Vig , Venkataramana Runkana

We introduce a non-wellfounded proof system for intuitionistic logic extended with inductive and co-inductive definitions, based on a syntax in which fixpoint formulas are annotated with explicit variables for ordinals. We explore the…

Logic in Computer Science · Computer Science 2026-05-13 Sebastian Enqvist

Purpose: This study extends the structural theory of finite commutative ternary $\Gamma$-semirings into a computational and categorical framework for explicit classification and constructive reasoning. Methods: Constraint-driven enumeration…

Rings and Algebras · Mathematics 2026-02-04 Chandrasekhar Gokavarapu , Dr D Madhusudhana Rao

Termination property of functions is an important issue in computability theory. In this paper, we show that repeated iterations of a function can induce an order amongst the elements of its domain set. Hasse diagram of the poset, thus…

Logic in Computer Science · Computer Science 2017-08-17 Abhinav Aggarwal , Padam Kumar