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We present a structured neural network architecture that is inspired by linear time-varying dynamical systems. The network is designed to mimic the properties of linear dynamical systems which makes analysis and control simple. The…

Robotics · Computer Science 2018-08-06 Alexander Broad , Ian Abraham , Todd Murphey , Brenna Argall

We introduce a new algebraic structure for multi-dimensional compositional embeddings, built on directional non-commutative monoidal operators. The core contribution of this work is this novel framework, which exhibits appealing theoretical…

Machine Learning · Computer Science 2025-05-22 Mahesh Godavarti

The production system (multidimensional object) is considered as a dynamic system with discrete time. Formalized: space (state of the object, control actions, goals, observed values, analytical estimates). Analytical estimates of the state…

Optimization and Control · Mathematics 2024-12-17 Sergei Masaev

Automatic music generation is an interdisciplinary research topic that combines computational creativity and semantic analysis of music to create automatic machine improvisations. An important property of such a system is allowing the user…

Sound · Computer Science 2020-03-03 Ke Chen , Gus Xia , Shlomo Dubnov

We present probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two different algorithms to exactly calculate the distribution of the results obtained by such…

Formal Languages and Automata Theory · Computer Science 2010-11-29 Tobias Marschall , Inke Herms , Hans-Michael Kaltenbach , Sven Rahmann

Advances in manufacturing and characterization of complex molecular systems have created a need for new methods for design at molecular length scales. Emerging approaches are increasingly relying on the use of Artificial Intelligence (AI),…

Soft Condensed Matter · Physics 2022-08-17 Dan Mendels , Fabian Byléhn , Timothy W. Sirk , Juan J. de Pablo

The constraints arising from DAG models with latent variables can be naturally represented by means of acyclic directed mixed graphs (ADMGs). Such graphs contain directed and bidirected arrows, and contain no directed cycles. DAGs with…

Machine Learning · Statistics 2012-07-24 Ilya Shpitser , Thomas S. Richardson , James M. Robins , Robin Evans

Digital memcomputing machines (DMMs) are a novel, non-Turing class of machines designed to solve combinatorial optimization problems. They can be physically realized with continuous-time, non-quantum dynamical systems with memory (time…

Emerging Technologies · Computer Science 2021-06-30 Yuan-Hang Zhang , Massimiliano Di Ventra

An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is presented. The algorithm manipulates the ordering of the variables with operations which very much resemble arc…

Artificial Intelligence · Computer Science 2013-03-25 Remco R. Bouckaert

This work establishes a robust mathematical foundation for compositional System Dynamics modeling, leveraging category theory to formalize and enhance the representation, analysis, and composition of system models. Here, System Dynamics…

Systems and Control · Electrical Eng. & Systems 2025-09-24 Xiaoyan Li , Evan Patterson , Patricia L. Mabry , Nathaniel D. Osgood

Deterministic Finite Automata (DFAs) are of central importance in automata theory. In view of how state diagrams for DFAs are defined using directed graphs, this leads us to introduce a generalization of DFAs related to a method widely used…

Formal Languages and Automata Theory · Computer Science 2025-06-18 John M. Campbell

This paper presents an approach to model melodies (and music pieces in general) as networks. Notes of a melody can be seen as nodes of a network that are connected whenever these are played in sequence. This creates a directed graph. By…

Sound · Computer Science 2016-11-18 Stefano Ferretti

Bond graphs can be used to build thermodynamically-compliant hierarchical models of biomolecular systems. As bond graphs have been widely used to model, analyse and synthesise engineering systems, this paper suggests that they can play the…

Molecular Networks · Quantitative Biology 2016-06-06 Peter Gawthrop , Edmund Crampin

Finding an embedding space for a linear approximation of a nonlinear dynamical system enables efficient system identification and control synthesis. The Koopman operator theory lays the foundation for identifying the nonlinear-to-linear…

Machine Learning · Computer Science 2020-04-28 Yunzhu Li , Hao He , Jiajun Wu , Dina Katabi , Antonio Torralba

The problem of modeling and control of multi-terminal high-voltage direct-current transmission systems is addressed in this paper, which contains five main contributions. First, to propose a unified, physically motivated, modeling framework…

Systems and Control · Computer Science 2016-09-13 Daniele Zonetti , Romeo Ortega , Abdelkrim Benchaib

When modeling complex robot systems such as branched robots, whose kinematic structures are a tree, current techniques often require modeling the whole structure from scratch, even when partial models for the branches are available. This…

Robotics · Computer Science 2024-07-23 Frederico Fernandes Afonso Silva , Bruno Vilhena Adorno

Modular design is a key challenge for enabling large-scale reuse of hardware modules. Unlike software, however, hardware designs correspond to physical circuits and inherit constraints from them. Timing constraints -- which cycle a signal…

Hardware Architecture · Computer Science 2023-04-24 Rachit Nigam , Pedro Henrique Azevedo De Amorim , Adrian Sampson

Arc-standard derivations over projective dependency trees can be interpreted as the incremental construction of lexicalized ordered trees with contiguous yields. Each \textsc{shift}, \textsc{leftarc}, and \textsc{rightarc} transition…

Computation and Language · Computer Science 2026-05-28 Zihao Huang , Ai Ka Lee , Jungyeul Park

Boolean networks are an important class of computational models for molecular interaction networks. Boolean canalization, a type of hierarchical clustering of the inputs of a Boolean function, has been extensively studied in the context of…

Molecular Networks · Quantitative Biology 2024-07-09 David Murrugarra , Elena S. Dimitrova

This article develops variational integrators for a class of underactuated mechanical systems using the theory of discrete mechanics. Further, a discrete optimal control problem is formulated for the considered class of systems and…

Systems and Control · Computer Science 2018-11-16 Siddharth H. Nair , Ravi N. Banavar