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Journal articles on the topic 'Universal models of computation'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Wootton, James R., and Jiannis K. Pachos. "Universal Quantum Computation with Abelian Anyon Models." Electronic Notes in Theoretical Computer Science 270, no. 2 (2011): 209–18. http://dx.doi.org/10.1016/j.entcs.2011.01.032.

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De las Cuevas, Gemma, Wolfgang Dür, Maarten Van den Nest, and Hans J. Briegel. "Completeness of classical spin models and universal quantum computation." Journal of Statistical Mechanics: Theory and Experiment 2009, no. 07 (2009): P07001. http://dx.doi.org/10.1088/1742-5468/2009/07/p07001.

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Šíma, Jiří, and Pekka Orponen. "Continuous-Time Symmetric Hopfield Nets Are Computationally Universal." Neural Computation 15, no. 3 (2003): 693–733. http://dx.doi.org/10.1162/089976603321192130.

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We establish a fundamental result in the theory of computation by continuous-time dynamical systems by showing that systems corresponding to so-called continuous-time symmetric Hopfield nets are capable of general computation. As is well known, such networks have very constrained Lyapunov-function controlled dynamics. Nevertheless, we show that they are universal and efficient computational devices, in the sense that any convergent synchronous fully parallel computation by a recurrent network of n discrete-time binary neurons, with in general asymmetric coupling weights, can be simulated by a

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Campos, Marcelino, and José M. Sempere. "Generating networks of genetic processors." Genetic Programming and Evolvable Machines 23, no. 1 (2021): 133–55. http://dx.doi.org/10.1007/s10710-021-09423-7.

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AbstractThe Networks of Genetic Processors (NGPs) are non-conventional models of computation based on genetic operations over strings, namely mutation and crossover operations as it was established in genetic algorithms. Initially, they have been proposed as acceptor machines which are decision problem solvers. In that case, it has been shown that they are universal computing models equivalent to Turing machines. In this work, we propose NGPs as enumeration devices and we analyze their computational power. First, we define the model and we propose its definition as parallel genetic algorithms.

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Suzuki, Ryotaro, Kosuke Mitarai, and Keisuke Fujii. "Computational power of one- and two-dimensional dual-unitary quantum circuits." Quantum 6 (January 24, 2022): 631. http://dx.doi.org/10.22331/q-2022-01-24-631.

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Quantum circuits that are classically simulatable tell us when quantum computation becomes less powerful than or equivalent to classical computation. Such classically simulatable circuits are of importance because they illustrate what makes universal quantum computation different from classical computers. In this work, we propose a novel family of classically simulatable circuits by making use of dual-unitary quantum circuits (DUQCs), which have been recently investigated as exactly solvable models of non-equilibrium physics, and we characterize their computational power. Specifically, we inve

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Qu, Yipeng, and Joohee Kim. "Enhancing Query Formulation for Universal Image Segmentation." Sensors 24, no. 6 (2024): 1879. http://dx.doi.org/10.3390/s24061879.

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Recent advancements in image segmentation have been notably driven by Vision Transformers. These transformer-based models offer one versatile network structure capable of handling a variety of segmentation tasks. Despite their effectiveness, the pursuit of enhanced capabilities often leads to more intricate architectures and greater computational demands. OneFormer has responded to these challenges by introducing a query-text contrastive learning strategy active during training only. However, this approach has not completely addressed the inefficiency issues in text generation and the contrast

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Shafahi, Ali, Mahyar Najibi, Zheng Xu, John Dickerson, Larry S. Davis, and Tom Goldstein. "Universal Adversarial Training." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 5636–43. http://dx.doi.org/10.1609/aaai.v34i04.6017.

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Standard adversarial attacks change the predicted class label of a selected image by adding specially tailored small perturbations to its pixels. In contrast, a universal perturbation is an update that can be added to any image in a broad class of images, while still changing the predicted class label. We study the efficient generation of universal adversarial perturbations, and also efficient methods for hardening networks to these attacks. We propose a simple optimization-based universal attack that reduces the top-1 accuracy of various network architectures on ImageNet to less than 20%, whi

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Ulyanov, Sergey, Andrey Reshetnikov, Olga Tyatyushkina, and Vladimir Korenkov. "Quantum software engineering. Pt. I: Quantum Circuit (Gate) Model based Computing – education Lectures and pedagogical workshop." System Analysis in Science and Education, no. 3 (2020) (September 30, 2020): 129–201. http://dx.doi.org/10.37005/2071-9612-2020-3-129-201.

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All the quantum algorithms are based on a certain quantum computing model, varying from the quantum circuit, one-way quantum computation, adiabatic quantum computation and topological quantum computation. These four models are equivalent in computational power; among them, the quantum circuit model is most frequently used. In the circuit model, it has been proved that arbitrary single-qubit rotations plus twoqubit controlled-NOT gates are universal, i.e. they can provide a set of gates to implement any quantum algorithm. This article discusses the goal for this research: it is to given a light

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Lowder, Chris, Chris Gilly, and Craig DeForest. "Field Line Universal relaXer (FLUX): A Fluxon Approach to Coronal Magnetic Field Modeling." Astrophysical Journal 965, no. 1 (2024): 13. http://dx.doi.org/10.3847/1538-4357/ad2845.

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Abstract We describe a novel method for modeling the global, steady solar wind using photospheric magnetic fields as a driving boundary condition. Prior wind models in this class include both rapid heuristic methods that use potential field extrapolation and variants thereof, trading rigor for computation speed, and detailed 3D magnetohydrodynamic (MHD) models that attempt to simulate the entire solar corona with a degree of physical rigor, but require large amounts of computation. The Field Line Universal relaXer, an open-source numerical code that implements the “fluxon” semi-Lagrangian appr

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Wu, Bujiao, Xiaoyang Wang, Xiao Yuan, Cupjin Huang, and Jianxin Chen. "Leakage Benchmarking for Universal Gate Sets." Entropy 26, no. 1 (2024): 71. http://dx.doi.org/10.3390/e26010071.

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Errors are common issues in quantum computing platforms, among which leakage is one of the most-challenging to address. This is because leakage, i.e., the loss of information stored in the computational subspace to undesired subspaces in a larger Hilbert space, is more difficult to detect and correct than errors that preserve the computational subspace. As a result, leakage presents a significant obstacle to the development of fault-tolerant quantum computation. In this paper, we propose an efficient and accurate benchmarking framework called leakage randomized benchmarking (LRB), for measurin

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Ignat, L., D. Pelletier, and F. Ilinca. "A universal formulation of two-equation models for adaptive computation of turbulent flows." Computer Methods in Applied Mechanics and Engineering 189, no. 4 (2000): 1119–39. http://dx.doi.org/10.1016/s0045-7825(99)00370-9.

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12

Maley, Carlo C. "DNA Computation: Theory, Practice, and Prospects." Evolutionary Computation 6, no. 3 (1998): 201–29. http://dx.doi.org/10.1162/evco.1998.6.3.201.

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L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also identified three broad categories of open questions for the field. First, is DNA capable of universal computation? Second, what kinds of algorithms can DNA implement? Third, can the error rates in the manipulations of the DNA be controlled enough to allow for useful computation? In the two years that have followed, theoretical work has shown that DNA is in fact capable of universal computation. Furthermore, algorithms

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Nehaniv, Chrystopher L., John Rhodes, Attila Egri-Nagy, et al. "Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2046 (2015): 20140223. http://dx.doi.org/10.1098/rsta.2014.0223.

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Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular

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Jones, Benjamin D. M., Noah Linden, and Paul Skrzypczyk. "The Hadamard gate cannot be replaced by a resource state in universal quantum computation." Quantum 8 (September 11, 2024): 1470. http://dx.doi.org/10.22331/q-2024-09-11-1470.

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We consider models of quantum computation that involve operations performed on some fixed resourceful quantum state. Examples that fit this paradigm include magic state injection and measurement-based approaches. We introduce a framework that incorporates both of these cases and focus on the role of coherence (or superposition) in this context, as exemplified through the Hadamard gate. We prove that given access to incoherent unitaries (those that are unable to generate superposition from computational basis states, e.g. CNOT, diagonal gates), classical control, computational basis measurement

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Zhan, Ye-Min, Yu-Ge Chen, Bin Chen, Ziqiang Wang, Yue Yu, and Xi Luo. "Universal topological quantum computation with strongly correlated Majorana edge modes." New Journal of Physics 24, no. 4 (2022): 043009. http://dx.doi.org/10.1088/1367-2630/ac5f87.

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Abstract Majorana-based quantum gates are not complete for performing universal topological quantum computation while Fibonacci-based gates are difficult to be realized electronically and hardly coincide with the conventional quantum circuit models. In reference Hu and Kane (2018 Phys. Rev. Lett. 120 066801), it has been shown that a strongly correlated Majorana edge mode in a chiral topological superconductor can be decomposed into a Fibonacci anyon τ and a thermal operator anyon ɛ in the tricritical Ising model. The deconfinement of τ and ɛ via the interaction between the fermion modes yield

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Kohler, Tamara, Stephen Piddock, Johannes Bausch, and Toby Cubitt. "Translationally Invariant Universal Quantum Hamiltonians in 1D." Annales Henri Poincaré 23, no. 1 (2021): 223–54. http://dx.doi.org/10.1007/s00023-021-01111-7.

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AbstractRecent work has characterized rigorously what it means for one quantum system to simulate another and demonstrated the existence of universal Hamiltonians—simple spin lattice Hamiltonians that can replicate the entire physics of any other quantum many-body system. Previous universality results have required proofs involving complicated ‘chains’ of perturbative ‘gadgets.’ In this paper, we derive a significantly simpler and more powerful method of proving universality of Hamiltonians, directly leveraging the ability to encode quantum computation into ground states. This provides new ins

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17

Jiang, Suxia, Jihui Fan, Yijun Liu, Yanfeng Wang, and Fei Xu. "Spiking Neural P Systems with Polarizations and Rules on Synapses." Complexity 2020 (July 9, 2020): 1–12. http://dx.doi.org/10.1155/2020/8742308.

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Spiking neural P systems are a class of computation models inspired by the biological neural systems, where spikes and spiking rules are in neurons. In this work, we propose a variant of spiking neural P systems, called spiking neural P systems with polarizations and rules on synapses (PSNRS P systems), where spiking rules are placed on synapses and neurons are associated with polarizations used to control the application of such spiking rules. The computation power of PSNRS P systems is investigated. It is proven that PSNRS P systems are Turing universal, both as number generating and accepti

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18

Postow, Brian, Kenneth Regan, and Carl H. Smith. "UPSILON: Universal Programming System with Incomplete Lazy Object Notation." Fundamenta Informaticae 50, no. 3-4 (2002): 325–59. https://doi.org/10.3233/fun-2002-503-406.

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This paper presents a new model of computation that differs from prior models in that it emphasizes data over flow control, has no named variables and has an object-oriented flavor. We prove that this model is a complete and confluent acceptable programming system and has a usable type theory. A new data synchronization primitive is introduced in order to achieve the above properties. Subtle variations of the model are shown to fall short of having all these necessary properties.

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19

Votto, Matteo, Johannes Zeiher, and Benoît Vermersch. "Universal quantum processors in spin systems via robust local pulse sequences." Quantum 8 (October 29, 2024): 1513. http://dx.doi.org/10.22331/q-2024-10-29-1513.

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We propose a protocol to realize quantum simulation and computation in spin systems with long-range interactions. Our approach relies on the local addressing of single spins with external fields parametrized by Walsh functions. This enables a mapping from a class of target Hamiltonians, defined by the graph structure of their interactions, to pulse sequences. We then obtain a recipe to implement arbitrary two-body Hamiltonians and universal quantum circuits. Performance guarantees are provided in terms of bounds on Trotter errors and total number of pulses. Additionally, Walsh pulse sequences

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20

Ulyanov, Sergey, Andrey Reshetnikov, and Olga Tyatyushkina. "Modelling of Grover’s quantum search algorithms: implementations of Simple quantum simulators on classical computers." System Analysis in Science and Education, no. 3 (2020) (September 30, 2020): 65–128. http://dx.doi.org/10.37005/2071-9612-2020-3-65-128.

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Models of Grover’s search algorithm is reviewed to build the foundation for the other algorithms. Thereafter, some preliminary modifications of the original algorithms by others are stated, that increases the applicability of the search procedure. A general quantum computation on an isolated system can be represented by a unitary matrix. In order to execute such a computation on a quantum computer, it is common to decompose the unitary into a quantum circuit, i.e., a sequence of quantum gates that can be physically implemented on a given architecture. There are different universal gate sets fo

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21

Parisi, Luciana. "Interactive Computation and Artificial Epistemologies." Theory, Culture & Society 38, no. 7-8 (2021): 33–53. http://dx.doi.org/10.1177/02632764211048548.

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What is algorithmic thought? It is not possible to address this question without first reflecting on how the Universal Turing Machine transformed symbolic logic and brought to a halt the universality of mathematical formalism and the biocentric speciation of thought. The article draws on Sylvia Wynter’s discussion of the sociogenic principle to argue that both neurocognitive and formal models of automated cognition constitute the epistemological explanations of the origin of the human and of human sapience. Wynter’s argument will be related to Gilbert Simondon’s reflections on ‘technical menta

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22

Kissinger, Aleks, and John van de Wetering. "Universal MBQC with generalised parity-phase interactions and Pauli measurements." Quantum 3 (April 26, 2019): 134. http://dx.doi.org/10.22331/q-2019-04-26-134.

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We introduce a new family of models for measurement-based quantum computation which are deterministic and approximately universal. The resource states which play the role of graph states are prepared via 2-qubit gates of the form exp⁡(−iπ2nZ⊗Z). When n=2, these are equivalent, up to local Clifford unitaries, to graph states. However, when n>2, their behaviour diverges in two important ways. First, multiple applications of the entangling gate to a single pair of qubits produces non-trivial entanglement, and hence multiple parallel edges between nodes play an important role in these generalis

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Shen, Yongshun, and Yuzhen Zhao. "Spiking Neural P Systems with Rules Dynamic Generation and Removal." Applied Sciences 13, no. 14 (2023): 8058. http://dx.doi.org/10.3390/app13148058.

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Spiking neural P systems (SNP systems), as computational models abstracted by the biological nervous system, have been a major research topic in biological computing. In conventional SNP systems, the rules in a neuron remain unchanged during the computation. In the biological nervous system, however, the biochemical reactions in a neuron are also influenced by factors such as the substances contained in it. Based on this motivation, this paper proposes SNP systems with rules dynamic generation and removal (RDGRSNP systems). In RDGRSNP systems, the application of rules leads to changes of the s

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Jones, Neil D., and Jakob Grue Simonsen. "Programs=data=first-class citizens in a computational world." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1971 (2012): 3305–18. http://dx.doi.org/10.1098/rsta.2011.0328.

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From a programming perspective, Alan Turing's epochal 1936 paper on computable functions introduced several new concepts, including what is today known as self-interpreters and programs as data , and invented a great many now-common programming techniques. We begin by reviewing Turing's contribution from a programming perspective; and then systematize and mention some of the many ways that later developments in models of computation (MOCs) have interacted with computability theory and programming language research. Next, we describe the ‘blob’ MOC: a recent stored-program computational model w

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Vranjkovic, Vuk, Predrag Teodorovic, and Rastislav Struharik. "Universal Reconfigurable Hardware Accelerator for Sparse Machine Learning Predictive Models." Electronics 11, no. 8 (2022): 1178. http://dx.doi.org/10.3390/electronics11081178.

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This study presents a universal reconfigurable hardware accelerator for efficient processing of sparse decision trees, artificial neural networks and support vector machines. The main idea is to develop a hardware accelerator that will be able to directly process sparse machine learning models, resulting in shorter inference times and lower power consumption compared to existing solutions. To the author’s best knowledge, this is the first hardware accelerator of this type. Additionally, this is the first accelerator that is capable of processing sparse machine learning models of different type

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Eberbach, Eugene. "On Completeness of Cost Metrics and Meta-Search Algorithms in $-Calculus." Fundamenta Informaticae 188, no. 2 (2023): 63–90. http://dx.doi.org/10.3233/fi-222142.

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In the paper we define three new complexity classes for Turing Machine undecidable problems inspired by the famous Cook/Levin’s NP-complete complexity class for intractable problems. These are U-complete (Universal complete), D-complete (Diagonalization complete) and H-complete (Hypercomputation complete) classes. In the paper, in the spirit of Cook/Levin/Karp, we started the population process of these new classes assigning several undecidable problems to them. We justify that some super-Turing models of computation, i.e., models going beyond Turing machines, are tremendously expressive and t

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Leyva-Acosta, Zoe, Eduardo Acuña Yeomans, and Francisco Hernandez-Quiroz. "An Additively Optimal Interpreter for Approximating Kolmogorov Prefix Complexity." Entropy 26, no. 9 (2024): 802. http://dx.doi.org/10.3390/e26090802.

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We study practical approximations of Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the optimality of the interpreter for this language as the reference machine for the Coding Theorem Method (CTM). This method is designed to address applications of algorithmic complexity that differ from the popular traditional lossless compression approach based on the principles of algorithmic probability. The chosen model of computation is proven to be suitable for this task, and a comparison to other models and methods is conducted. Our finding

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Miró-Zárate, Luis Angel, Igor Loboda, Juan Luis Pérez-Ruiz, and Miguel Toledo-Velázquez. "Estimation and monitoring of unmeasured gas turbine variables." Transactions of the Canadian Society for Mechanical Engineering 43, no. 1 (2019): 26–37. http://dx.doi.org/10.1139/tcsme-2017-0009.

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This work proposes a universal data-driven approach to compute and monitor gas turbine unmeasured variables. To this end, a large amount of unmeasured and measured data is first computed at steady state for both baseline and faulty engine conditions using a nonlinear thermodynamic model. On the data generated, polynomial models that relate the unmeasured quantities with the measured variables are then determined. These data-driven models allow the computation of unmeasured variables and their deviations. Accuracy analysis is conducted separately for baseline and current estimates of unmeasured

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JIMÉNEZ, JAVIER, AMABLE LIÑÁN, MICHAEL M. ROGERS, and FRANCISCO J. HIGUERA. "A priori testing of subgrid models for chemically reacting non-premixed turbulent shear flows." Journal of Fluid Mechanics 349 (October 25, 1997): 149–71. http://dx.doi.org/10.1017/s0022112097006733.

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The β-assumed-p.d.f. approximation of Cook & Riley (1994) is tested as a subgrid model for the LES computation of non-premixed turbulent reacting flows, in the limit of infinitely fast chemistry, for two plane constant-density turbulent mixing layers with different degrees of intermittency. Excellent results are obtained in the computation of plane-averaged properties, such as product mass fractions and relatively high powers of the temperature, and even of the p.d.f. of the conserved scalar itself. In all these cases the errors are small enough to be useful in practical applications. The

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Il’ichev, V. G. "Universal stock constants in models of competition." Mathematical Models and Computer Simulations 8, no. 1 (2016): 73–83. http://dx.doi.org/10.1134/s2070048216010038.

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Hien Le Tat, Nguyen Duy Anh, and Nguyen Thi Ngoc Hoa. "Numerical Investigate the Effect of Turbulence Models on the CFD Computation of Submarine Resistance." CFD Letters 16, no. 10 (2024): 126–39. http://dx.doi.org/10.37934/cfdl.16.10.126139.

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Up to now, there is no developed ‘universal’ turbulence model in CFD simulation, so employing an appropriate turbulence model is crucial for accurately predicting the hydrodynamics of a ship, especially for submarines. This study focuses on investigating the impact of turbulence models on the predicted results in frictional and pressure resistance components and flow features around the submarine at different ship velocities by the CFD method. Four various turbulence models consisting of the Reynolds Stress Model, realizable k-ε two-layer, standard k-ω, and SST k-ω turbulence models are invest

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Su, Hua, Chun-lin Gong, and Liang-xian Gu. "A Universal MDO Framework Based on the Adaptive Discipline Surrogate Model." International Journal of Aerospace Engineering 2018 (November 27, 2018): 1–14. http://dx.doi.org/10.1155/2018/9139267.

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High time-consuming computation has become an obvious characteristic of the modern multidisciplinary design optimization (MDO) solving procedure. To reduce the computing cost and improve solving environment of the traditional MDO solution method, this article introduces a novel universal MDO framework based on the support of adaptive discipline surrogate model with asymptotical correction by discriminative sampling. The MDO solving procedure is decomposed into three parts: framework level, architecture level, and discipline level. Framework level controls the MDO solving procedure and carries

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Rung, T., H. Lübcke, and F. Thiele. "Universal wall-boundary conditions for turbulence-transport models." ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 81, S3 (2001): 481–82. http://dx.doi.org/10.1002/zamm.20010811520.

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AKL, SELIM G. "THREE COUNTEREXAMPLES TO DISPEL THE MYTH OF THE UNIVERSAL COMPUTER." Parallel Processing Letters 16, no. 03 (2006): 381–403. http://dx.doi.org/10.1142/s012962640600271x.

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It is shown that the concept of a Universal Computer cannot be realized. Specifically, instances of a computable function [Formula: see text] are exhibited that cannot be computed on any machine [Formula: see text] that is capable of only a finite and fixed number of operations per step. This remains true even if the machine [Formula: see text] is endowed with an infinite memory and the ability to communicate with the outside world while it is attempting to compute [Formula: see text]. It also remains true if, in addition, [Formula: see text] is given an indefinite amount of time to compute [F

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Behme, Christina. "Can evolution provide perfectly optimal solutions for a universal model of reading?" Behavioral and Brain Sciences 35, no. 5 (2012): 279–80. http://dx.doi.org/10.1017/s0140525x12000015.

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AbstractFrost has given us good reason to question the universality of existing computational models of reading. Yet, he has not provided arguments showing that all languages share fundamental and invariant reading universals. His goal of outlining the blueprint principles for a universal model of reading is premature. Further, it is questionable whether natural evolution can provide the optimal solutions that Frost invokes.

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Tominaga, Kazuto, Tooru Watanabe, Keiji Kobayashi, Masaki Nakamura, Koji Kishi, and Mitsuyoshi Kazuno. "Modeling Molecular Computing Systems by an Artificial Chemistry—Its Expressive Power and Application." Artificial Life 13, no. 3 (2007): 223–47. http://dx.doi.org/10.1162/artl.2007.13.3.223.

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Artificial chemistries are mainly used to construct virtual systems that are expected to show behavior similar to living systems. In this study, we explore possibilities of applying an artificial chemistry to modeling natural biochemical systems—or, to be specific, molecular computing systems—and show that it may be a useful modeling tool for molecular computation. We previously proposed an artificial chemistry based on string pattern matching and recombination. This article first demonstrates that this artificial chemistry is computationally universal if it has only rules that have one reacta

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Shopov, Antonio. "Theoretical-Computation Conception for Forecasting on Corrosion Influence into Steel Elements at Sustainable Development." International Journal of Innovative Technology and Exploring Engineering 8, no. 8 (2019): 2253–61. https://doi.org/10.5281/zenodo.14581291.

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The majority of existing numerical methods for predicting the effect of corrosion on steel elements are oriented using experimental results and established dependencies. It is wrong to think that solving a corrosion problem will be achieved automatically by applying several numerical models. First, it is necessary to carry out, systemize and process numerical and statistically determined number of experimental observations, measurements and results. Under the same corrosive conditions, different mathematical calculation models can be created, but each of these models will be a private solution

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Paun, Gheorghe, and Takashi Yokomori. "Simulating H Systems by P Systems." JUCS - Journal of Universal Computer Science 6, no. (1) (2000): 178–93. https://doi.org/10.3217/jucs-006-01-0178.

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H systems are DNA computing models, based on the operation of splicing. P systems are membrane computing models, where objects can evolve in parallel in a hierarchical membrane structure. In particular, the objects can be strings and the evolution rules can be based on splicing. Both H systems with certain controls on the use of splicing rules and P systems of various types are known to be computationally universal, that is, they characterize the recursively ennumerable languages. So, they are equivalent as the generative power. The present paper presents a direct simulation of some controlled

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Strodthoff, Nils, Patrick Wagner, Markus Wenzel, and Wojciech Samek. "UDSMProt: universal deep sequence models for protein classification." Bioinformatics 36, no. 8 (2020): 2401–9. http://dx.doi.org/10.1093/bioinformatics/btaa003.

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Abstract Motivation Inferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification are tailored to single classification tasks and rely on handcrafted features, such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple fine-tuning step. Results We put for

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Sanguineti, Marcello. "Universal Approximation by Ridge Computational Models and Neural Networks: A Survey." Open Applied Mathematics Journal 2, no. 1 (2008): 31–58. http://dx.doi.org/10.2174/1874114200802010031.

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Stacewicz, Paweł. "Analogicity in Computer Science. Methodological Analysis." Studies in Logic, Grammar and Rhetoric 63, no. 1 (2020): 69–86. http://dx.doi.org/10.2478/slgr-2020-0028.

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AbstractAnalogicity in computer science is understood in two, not mutually exclusive ways: 1) with regard to the continuity feature (of data or computations), 2) with regard to the analogousness feature (i.e. similarity between certain natural processes and computations). Continuous computations are the subject of three methodological questions considered in the paper: 1a) to what extent do their theoretical models go beyond the model of the universal Turing machine (defining digital computations), 1b) is their computational power greater than that of the universal Turing machine, 1c) under wh

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Wang, Liping, Xiyu Liu, and Yuzhen Zhao. "Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses." Computational Intelligence and Neuroscience 2021 (August 25, 2021): 1–15. http://dx.doi.org/10.1155/2021/3285719.

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The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron’s firing. In this work, in order to improve computing performance, the weights and delays are introduced to the NSNP system, and universal nonlinear spiking neural P systems with delays and weights on synapses (NSNP-DW) are proposed. Weights are treated as multiplicative constants by which the number of spikes is increased when transiting across synapses, and delays take into account the speed at w

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Shin, Kyuyong, Hanock Kwak, Su Young Kim, et al. "Scaling Law for Recommendation Models: Towards General-Purpose User Representations." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (2023): 4596–604. http://dx.doi.org/10.1609/aaai.v37i4.25582.

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Recent advancement of large-scale pretrained models such as BERT, GPT-3, CLIP, and Gopher, has shown astonishing achievements across various task domains. Unlike vision recognition and language models, studies on general-purpose user representation at scale still remain underexplored. Here we explore the possibility of general-purpose user representation learning by training a universal user encoder at large scales. We demonstrate that the scaling law is present in user representation learning areas, where the training error scales as a power-law with the amount of computation. Our Contrastive

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Fetzer, Valerie, Marcel Keller, Sven Maier, Markus Raiber, Andy Rupp, and Rebecca Schwerdt. "PUBA: Privacy-Preserving User-Data Bookkeeping and Analytics." Proceedings on Privacy Enhancing Technologies 2022, no. 2 (2022): 447–516. http://dx.doi.org/10.2478/popets-2022-0054.

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Abstract In this paper we propose Privacy-preserving User-data Bookkeeping & Analytics (PUBA), a building block destined to enable the implementation of business models (e.g., targeted advertising) and regulations (e.g., fraud detection) requiring user-data analysis in a privacy-preserving way. In PUBA, users keep an unlinkable but authenticated cryptographic logbook containing their historic data on their device. This logbook can only be updated by the operator while its content is not revealed. Users can take part in a privacy-preserving analytics computation, where it is ensured that th

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JAROSZ, GAJA. "Implicational markedness and frequency in constraint-based computational models of phonological learning." Journal of Child Language 37, no. 3 (2010): 565–606. http://dx.doi.org/10.1017/s0305000910000103.

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ABSTRACTThis study examines the interacting roles of implicational markedness and frequency from the joint perspectives of formal linguistic theory, phonological acquisition and computational modeling. The hypothesis that child grammars are rankings of universal constraints, as in Optimality Theory (Prince & Smolensky, 1993/2004), that learning involves a gradual transition from an unmarked initial state to the target grammar, and that order of acquisition is guided by frequency, along the lines of Levelt, Schiller & Levelt (2000), is investigated. The study reviews empirical findings

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Zhong 钟, Yang 阳., Hongyu 宏宇 Yu 于, Jihui 吉辉 Yang 杨, Xingyu 星宇 Guo 郭, Hongjun 红军 Xiang 向, and Xingao 新高 Gong 龚. "Universal Machine Learning Kohn–Sham Hamiltonian for Materials." Chinese Physics Letters 41, no. 7 (2024): 077103. http://dx.doi.org/10.1088/0256-307x/41/7/077103.

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Abstract While density functional theory (DFT) serves as a prevalent computational approach in electronic structure calculations, its computational demands and scalability limitations persist. Recently, leveraging neural networks to parameterize the Kohn–Sham DFT Hamiltonian has emerged as a promising avenue for accelerating electronic structure computations. Despite advancements, challenges such as the necessity for computing extensive DFT training data to explore each new system and the complexity of establishing accurate machine learning models for multi-elemental materials still exist. Add

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Morimae, Tomoyuki, and Suguru Tamaki. "Fine-grained quantum computational supremacy." quantum Information and Computation 19, no. 13&14 (2019): 1089–115. http://dx.doi.org/10.26421/qic19.13-14-2.

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(pp1089-1115) Tomoyuki Morimae and Suguru Tamaki doi: https://doi.org/10.26421/QIC19.13-14-2 Abstracts: Output probability distributions of several sub-universal quantum computing models cannot be classically efficiently sampled unless some unlikely consequences occur in classical complexity theory, such as the collapse of the polynomial-time hierarchy. These results, so called quantum supremacy, however, do not rule out possibilities of super-polynomial-time classical simulations. In this paper, we study ``fine-grained" version of quantum supremacy that excludes some exponential-time classica

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Wang, Wenfeng, Xi Chen, Guiwei Zhang, et al. "Precision Security: Integrating Video Surveillance with Surrounding Environment Changes." Complexity 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/2959030.

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Video surveillance plays a vital role in maintaining the social security although, until now, large uncertainty still exists in danger understanding and recognition, which can be partly attributed to intractable environment changes in the backgrounds. This article presents a brain-inspired computing of attention value of surrounding environment changes (EC) with a processes-based cognition model by introducing a ratio valueλof EC-implications within considered periods. Theoretical models for computation of warning level of EC-implications to the universal video recognition efficiency (quantifi

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Müller, B. "Is Finite-Size Scaling Universal for Ising Models?" International Journal of Modern Physics C 09, no. 04 (1998): 585–89. http://dx.doi.org/10.1142/s0129183198000480.

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The sensitivity on shape and boundaries at the Curie point of the universal critical ratio LdM2/χ for the Ising model is confirmed by a comparison of square and rectangular lattices. Tests with three different algorithms give the same results for the universal critical ratio on various lattice types and always the same dependence on the system's aspect ratio.

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Sarkar, Aritra, Zaid Al-Ars, and Koen Bertels. "Estimating Algorithmic Information Using Quantum Computing for Genomics Applications." Applied Sciences 11, no. 6 (2021): 2696. http://dx.doi.org/10.3390/app11062696.

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Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target metrics computable under realistic assumptions. The universal prior distribution for the automata is obtained as a quantum superposition, which is further conditioned to estimate the metrics. Specific cases are explored where the quantum implementation offe

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