Relevant bibliographies by topics / Computational models

Academic literature on the topic 'Computational models'

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Published: 4 June 2021
Last updated: 11 March 2023

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Journal articles on the topic "Computational models"

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Miłkowski, Marcin. "Computational Mechanisms and Models of Computation." Philosophia Scientae, no. 18-3 (October 1, 2014): 215–28. http://dx.doi.org/10.4000/philosophiascientiae.1019.

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Humphreys, Paul. "Computational Models." Philosophy of Science 69, S3 (September 2002): S1—S11. http://dx.doi.org/10.1086/341763.

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Fellous, Jean-Marc, and Christiane Linster. "Computational Models of Neuromodulation." Neural Computation 10, no. 4 (May 1, 1998): 771–805. http://dx.doi.org/10.1162/089976698300017476.

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Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.
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Siegel, David A. "Analyzing Computational Models." American Journal of Political Science 62, no. 3 (June 6, 2018): 745–59. http://dx.doi.org/10.1111/ajps.12364.

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Hilgers, M. G. "Computational finance models." IEEE Potentials 19, no. 5 (2001): 8–10. http://dx.doi.org/10.1109/45.890082.

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White, D. R., J. C. Buckland-Wright, R. V. Griffith, L. N. Rothenberg, C. K. Showwalter, G. Williams, I. J. Wilson, and M. Zankl. "8. Computational Models." Reports of the International Commission on Radiation Units and Measurements os-25, no. 1 (June 1992): 35–45. http://dx.doi.org/10.1093/jicru_os25.1.35.

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White, D. R., J. C. Buckland-Wright, R. V. Griffith, L. N. Rothenberg, C. K. Showwalter, G. Williams, I. J. Wilson, and M. Zankl. "8. Computational Models." Journal of the International Commission on Radiation Units and Measurements os25, no. 1 (June 15, 1992): 35–45. http://dx.doi.org/10.1093/jicru/os25.1.35.

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Wienke, B. R. "Computational decompression models." International Journal of Bio-Medical Computing 21, no. 3-4 (November 1987): 205–21. http://dx.doi.org/10.1016/0020-7101(87)90088-2.

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Blakey, Ed. "Computational Complexity in Non-Turing Models of Computation." Electronic Notes in Theoretical Computer Science 270, no. 1 (February 2011): 17–28. http://dx.doi.org/10.1016/j.entcs.2011.01.003.

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Shi, Qiangqiang, Yiyang Yang, and Xiaolin Li. "EFFICIENCY OF GPU COMPUTATION ON THREE COMPUTATIONAL MODELS." Far East Journal of Applied Mathematics 94, no. 4 (June 29, 2016): 285–316. http://dx.doi.org/10.17654/am094040285.

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Dissertations / Theses on the topic "Computational models"

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Erriquez, Elisabetta. "Computational models of trust." Thesis, University of Liverpool, 2012. http://livrepository.liverpool.ac.uk/7433/.

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Trust and reputation are key issues in the multi-agent systems domain. As in human societies, software agents must interact with other agents in settings where there is the possibility that they can be exploited. This suggests the need for theoretical and computational models of trust and reputation that can be used by software agents, and accordingly, much research has investigated this issue. The first part of this thesis investigates the conjecture that agents who make decisions in scenarios where trust is important can benefit from the use of a social structure, representing the social relationships that exist between agents. To this end, we present techniques that can be used by agents to initially build and then progressively update such a structure in the light of experience. As the agents interact with other agents they gather information about interactions and relationships in order to build the network of agents and to better understand their social environment. We also show empirical evidence that a trust model enhanced with a social structure representation, used to gather additional information to select trustworthy agents for an agent’s interactions, can improve the trust model’s performance. In the second part of this thesis, we concentrate on the context of coalition formation. Coalition stability is a crucial issue. Stability is the motivation of an agent’s refusal to break from the original coalition and form a new one. Lack of trust in some of the coalition members could induce one agent to leave the coalition. Therefore we address the current model’s limitation by introducing an abstract framework that allows agents to form distrust-free coalitions. Moreover we present measures to evaluate the trustworthiness of the agent with respect to the whole society or to a particular coalition. We also describe a way to combine the trust and distrust relationships to form coalitions which are still distrust-free.
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Casarin, Stefano. "Mathematical models in computational surgery." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS008/document.

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La chirurgie informatisée est une science nouvelle dont le but est de croiser la chirurgie avec les sciences de l’informatique afin d’aboutir à des améliorations significatives dans les deux domaines. Avec l’évolution des nouvelles techniques chirurgicales, une collaboration étroite entre chirurgiens et chercheurs est devenue à la fois inévitable et essentielle à l’optimisation des soins chirurgicaux. L’utilisation de modèles mathématiques est la pierre angulaire de ce nouveau domaine. Cette thèse démontre comment une approche systématique d’un problème clinique nous a amenés à répondre à des questions ouvertes dans le domaine chirurgical en utilisant des modèles mathématiques à grande échelle. De manière générale, notre approche inclut (i) une vision générale du problème, (ii) le ciblage du/des système(s) physiologique(s) à étudier pour y répondre, et (iii) un effort de modélisation mathématique, qui a toujours été poussé par la recherche d’un compromis entre complexité du système étudié et réalité physiologique. Nous avons consacré la première partie de cette thèse à l’optimisation des conditions limites à appliquer à un bio-réacteur utilisé pour démultiplier le tissu pulmonaire provenant d’un donneur. Un modèle géométrique de l’arbre trachéo-bronchique couplé à un modèle de dépôt de soluté nous a permis de déterminer l’ensemble des pressions à appliquer aux pompes servant le bio-réacteur afin d’obtenir une distribution optimale des nutriments à travers les cultures de tissus. Nous avons consacré la seconde partie de cette thèse au problème de resténose des greffes de veines utilisées pour contourner une occlusion artérielle. Nous avons reproduit l’apparition de resténose grâce à plusieurs modèles mathématiques qui permettent d’étudier les preuves cliniques et de tester des hypothèses cliniques avec un niveau croissant de complexité et de précision. Pour finir, nous avons développé un cadre de travail robuste pour tester les effets des thérapies géniques afin de limiter la resténose. Une découverte intéressante a été de constater qu’en contrôlant un groupe de gènes spécifique, la perméabilité à la lumière double après un mois de suivi. Grace aux résultats obtenus, nous avons démontré que la modélisation mathématique peut servir de puissant outil pour l’innovation chirurgicale
Computational surgery is a new science that aims to intersect surgery and computational sciences in order to bring significant improvements in both fields. With the evolution of new surgical techniques, a close collaboration between surgeons and computational scientists became unavoidable and also essential to optimize surgical care. A large usage of mathematical models is the cornerstone in this new field. The present thesis shows how a systematic approach to a clinical problem brought us to answer open questions in the field of surgery by using mathematical models on a large scale. In general, our approach includes (i) an overview of the problem, (ii) the individuation of which physiological system/s is/are to be studied to address the question, and (iii) a mathematical modeling effort, which has been always driven by the pursue of a compromise between system complexity and closeness to the physiological reality. In the first part, we focused on the optimization of the boundary conditions to be applied to a bioreactor used to re-populate lung tissue from donor. A geometrical model of tracheobronchial tree combined with a solute deposition model allowed us to retrieve the set of pressures to be applied to the pumps serving the bioreactor in order to reach an optimal distribution of nourishment across the lung scaffold. In the second part, we focused on the issue of post-surgical restenosis of vein grafts used to bypass arterial occlusions. We replicated the event of restenosis with several mathematical models that allow us to study the clinical evidences and to test hypothesis with an escalating level of complexity and accuracy. Finally, we developed a solid framework to test the effect of gene therapies aimed to limit the restenosis. Interestingly, we found that by controlling a specific group of genes, the lumen patency is double after a month of follow-up. With the results achieved, we proved how mathematical modeling can be used as a powerful tool for surgical innovation
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Alzaidi, Samara Samir. "Computational Models of Cerebral Hemodynamics." Thesis, University of Canterbury. Mechanical Engineering, 2009. http://hdl.handle.net/10092/3159.

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The cerebral tissue requires a constant supply of oxygen and nutrients. This is maintained through delivering a constant supply of blood. The delivery of sufficient blood is preserved by the cerebral vasculature and its autoregulatory function. The cerebral vasculature is composed of the Circle of Willis (CoW), a ring-like anastomoses of arteries at the base of the brain, and its peripheral arteries. However, only 50% of the population have a classical complete CoW network. This implies that the route of blood flow through the cerebral vasculature is different and dependent on where the blood is needed most in the brain. Autoregulation is a mechanism held by the peripheral arteries and arterioles downstream of the CoW. It ensures the delivery of the essential amount of cerebral blood flow despite changes in the arterial perfusion pressure, through the vasoconstriction and vasodilation of the vessels. The mechanisms that control the vessels’ vasomotion could be attributed to myogenic, metabolic, neurogenic regulation or a combination of all three. However, the variations in the CoW structure, combined with different pathological conditions such as hypertension, a stenosis or an occlusion in one or more of the supplying cerebral arteries may alter, damage or abolish autoregulation, and consequently result in a stroke. Stroke is the most common cerebrovascular disease that affects millions of people in the world every year. Therefore, it is essential to understand the cerebral hemodynamics via mathematical modelling of the cerebral vasculature and its regulation mechanisms. This thesis presents the developed model of the cerebral vasculature coupled with the different forms of autoregulation mechanisms. The model was developed over multiple stages. First, a linear model of the CoW was developed, where the peripheral vessels downstream of the CoW efferent arteries are represented as lumped parameter variable resistances. The autoregulation function in the efferent arteries was modelled using a PI controller, and a metabolic model was added to the lumped peripheral variable resistances. The model was then modified so the pressure losses encountered at the CoW bifurcations, and the vessels’ tortuosity are taken into account resulting in a non-linear system. A number of cerebral autoregulation models exist in the literature, however, no model combines a fully populated arterial tree with dynamic autoregulation. The final model presented in this thesis was built by creating an asymmetric binary arterial vascular tree to replace the lumped resistance parameters for the vasculature network downstream of each of the CoW efferent arteries. The autoregulation function was introduced to the binary arterial tree by implementing the myogenic and metabolic mechanisms which are active in the small arteries and arterioles of the binary arterial tree. The myogenic and metabolic regulation mechanisms were both tested in the model. The results indicate that because of the low pressures experienced by the arterioles downstream of the arterial tree, the myogenic mechanism, which is hypothesised by multiple researchers as the main driver of autoregulation, does not provide enough regulation of the arterioles’ diameters to support autoregulation. The metabolic model showed that it can provide sufficient changes in the arterioles’ diameters, which produces a vascular resistance that support the constancy of the autoregulation function. The work carried out for this research has the potential of being a significant clinical tool to evaluate patient-specific cases when combined with the graphical user interfaces provided. The research and modelling performed was done as part of the Brain Group of the Centre of Bioengineering at the University of Canterbury.
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Ng, Khin Hua. "Computational models of belief propagation." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/55283.

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In this thesis we aim to gain better understanding on the working of the belief propagation algorithm designed for graphical models in other computational frameworks like the neural systems, as well as the error associated with loopy belief propagation in Bayesian networks. In the first part, we examine a few recent neural computational models of belief propagation and highlight the significance of these models that demonstrate the viability of performing belief propagation using neural computations by transforming it into a dynamical system. We also propose the idea of implementing the belief propagation in computational models like the Hopfield network through free energy minimisation. It is widely known that exact inference in loopy graphs is computationally difficult and thus there has been a lot of effort spent in the area of developing practical approximate inference algorithms. Loopy belief propagation is a widely used approximate inference algorithm for graphical models. In the second part of this thesis, we analyse the loopy error and propose two exact inference algorithms using belief propagation with loop correction for Bayesian networks with generic loops. We also propose a new approximate inference method called the 2-Pass loopy belief propagation and demonstrate empirically its potential for use as a fast approximate inference algorithm with comparable accuracy to standard loopy belief propagation. We also discuss issues related to its application as an approximate inference method.
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Stegle, Oliver. "Probabilistic models in computational biology." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611560.

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Jackson, Antony. "Computational models of financial markets." Thesis, University of Leicester, 2014. http://hdl.handle.net/2381/28753.

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The three chapters of this thesis share the common theme of computational approaches to modeling financial markets. Chapter 1, “Market Ecologies: The Interaction and Survival of Technical Trading Strategies”, finds its place in the boundedly-rational heterogeneous agent literature. Market prices result from the interaction of fundamental and technical trading strategies. We show that the way in which traders process information is critical in determining the long-run profitability of individual strategies. More realistic auction settings— in which price information is incorporated into trading methods in “real time”—demand computationally demanding techniques. The main conclusion of the chapter is that contrarian technical traders inadvertently mimic the role of arbitrageurs in more realistic auction settings. Chapter 2, “Capital Allocation in a Delegated Trading Model”, develops a model of capital allocation that removes the need for full mean-variance optimization of the firm-level portfolio. The strategies explored within the artificial setting of Chapter 1 are used to test the model against empirical foreign exchange data. We observe that the proposed capital allocation scheme yields economically and statistically significant returns, even when traders choose rules without the benefit of hindsight. Chapter 3, “Portfolio Choice: The Costs and Benefits of Asymmetric Information”, continues the theme of artificial markets, with the auction process departing from the fictitious auctioneer of Chapter 1, toward a market making model in which risk-neutral dealers quote bid-ask spreads to compensate them for the losses incurred by trading with informed agents. We obtain the intriguing result that, in multiple markets, there is an “optimal” level of inside information. In individual markets, portfolio managers incur higher transaction costs as asymmetric information increases, but benefit from an externality at the portfolio level, as inside information aids price discovery.
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Frankenstein, William. "Computational Models of Nuclear Proliferation." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/782.

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This thesis utilizes social influence theory and computational tools to examine the disparate impact of positive and negative ties in nuclear weapons proliferation. The thesis is broadly in two sections: a simulation section, which focuses on government stakeholders, and a large-scale data analysis section, which focuses on the public and domestic actor stakeholders. In the simulation section, it demonstrates that the nonproliferation norm is an emergent behavior from political alliance and hostility networks, and that alliances play a role in current day nuclear proliferation. This model is robust and contains second-order effects of extended hostility and alliance relations. In the large-scale data analysis section, the thesis demonstrates the role that context plays in sentiment evaluation and highlights how Twitter collection can provide useful input to policy processes. It first highlights the results of an on-campus study where users demonstrated that context plays a role in sentiment assessment. Then, in an analysis of a Twitter dataset of over 7.5 million messages, it assesses the role of ‘noise’ and biases in online data collection. In a deep dive analyzing the Iranian nuclear agreement, we demonstrate that the middle east is not facing a nuclear arms race, and show that there is a structural hole in online discussion surrounding nuclear proliferation. By combining both approaches, policy analysts have a complete and generalizable set of computational tools to assess and analyze disparate stakeholder roles in nuclear proliferation.
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Eades, Patrick Fintan. "Uncertainty Models in Computational Geometry." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23909.

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In recent years easily and cheaply available internet-connected devices have enabled the collection of vast amounts of data, which has driven a continued interest in efficient, elegant combinatorial algorithms with mathematical guarantees. Much of this data contains an inherent element of uncertainty; whether because of imperfect measurements, because the data contains predictions about the future, or because the data is derived from machine learning algorithms which are inherently probabilistic. There is therefore a need for algorithms which include uncertainty in their definition and give answers in terms of that uncertainty. Questions about the most likely solution, the solution with lowest expected cost or a solution which is correct with high probability are natural here. Computational geometry is the sub-field of theoretical computer science concerned with developing algorithms and data structures for geometric problems, that is problems involving points, distances, angles and shapes. In computational geometry uncertainty is included in the location of the input points, or in which potential points are included in the input. The study of uncertainty in computational geometry is relatively recent; earlier research concerned imprecise points, which are known to appear somewhere in a geometric region. More recently the focus has been on points whose location, or presence, is given by a probability distribution. In this thesis we describe the most commonly used uncertainty models which are the subject of ongoing research in computational geometry. We present specific problems in those models and present new results, both positive and negative. In Chapter 3 we consider universal solutions, and show a new lower bound on the competitive ratio of the Universal Traveling Salesman Problem. In Chapter 4 we describe how to determine if two moving entities are ever mutually visible, and how data structures can be repeatedly queried to simulate uncertainty. In Chapter 5 we describe how to construct a graph on uncertain points with high probability of being a geometric spanner, an example of redundancy protecting against uncertainty. In Chapter 6 we introduce the online ply maintenance problem, an online problem where uncertainty can be reduced at a cost, and give an optimal algorithm.
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Bashar, Hasanain. "Meta-modelling of intensive computational models." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/13667/.

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Engineering process design for applications that use computationally intensive nonlinear dynamical systems can be expensive in time and resources. The presented work reviews the concept of a meta-model as a way to improve the efficiency of this process. The proposed meta-model will have a computational advantage in implementation over the computationally intensive model therefore reducing the time and resources required to design an engineering process. This work proposes to meta-model a computationally intensive nonlinear dynamical system using reduced-order linear parameter varying system modelling approach with local linear models in velocity based linearization form. The parameters of the linear time-varying meta-model are blended using Gaussian Processes regression models. The meta-model structure is transparent and relates directly to the dynamics of the computationally intensive model while the velocity-based local linear models faithfully reproduce the original system dynamics anywhere in the operating space of the system. The non-parametric blending of the meta-model local linear models by Gaussian Processes regression models is ideal to deal with data sparsity and will provide uncertainty information about the meta-model predictions. The proposed meta-model structure has been applied to second-order nonlinear dynamical systems, a small sized nonlinear transmission line model, medium sized fluid dynamics problem and the computationally intensive nonlinear transmission line model of order 5000.
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Calude, Elena. "Automata-Theoretic Models for Computational Complementarity." Thesis, University of Auckland, 1997. http://hdl.handle.net/2292/1915.

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The purpose of this Thesis is to study, from the mathematical point of view, a new type of questions about finite automata, questions motivated by looking at automata as toy models of physical particles. Working along the line of research initiated by Moore, two computational complementarity principles are studied, (for finite-deterministic, complete or incomplete, nondeterministic-automata with outputs but no initial states) both theoretically and experimentally; they mimic the physical complementarity and the Einstein-Podolsky-Rosen effect. Automata are studied via simulations (informally, the automaton A is simulated by the automaton B if B can perform all computations A can execute and produces the same outputs; two automata are equivalent in case they simulate each other). A new type of minimization problem will be solved and the solution is proved to be unique up to an isomorphism; the minimal automaton equivalent to a given automaton can be constructed only in terms of outputs for deterministic complete or incomplete automata, but one needs the whole internal machinery for nondeterministic automata. It happens that minimal automata are exactly the automata which may feature computational complementarity. Even if the original motivation will remain only metaphorical, the physical motivation was good to suggest new definitions and constructions (simulation, universality, complementarity) leading to new mathematical results (existence of universal finite automaton, solving in a new way the minimalization problem for nondeterministic automata).
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Books on the topic "Computational models"

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Senthilkumar, Muthukrishnan, Vijayalakshmi Ramasamy, Shina Sheen, C. Veeramani, Anthony Bonato, and Lynn Batten, eds. Computational Intelligence, Cyber Security and Computational Models. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0251-9.

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Krishnan, G. Sai Sundara, R. Anitha, R. S. Lekshmi, M. Senthil Kumar, Anthony Bonato, and Manuel Graña, eds. Computational Intelligence, Cyber Security and Computational Models. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1680-3.

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Schmajuk, Nestor, ed. Computational Models of Conditioning. Cambridge: Cambridge University Press, 2009. http://dx.doi.org/10.1017/cbo9780511760402.

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Hecht-Nielsen, Robert, and Thomas McKenna, eds. Computational Models for Neuroscience. London: Springer London, 2003. http://dx.doi.org/10.1007/978-1-4471-0085-0.

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Bolc, Leonard, ed. Computational Models of Learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-82742-6.

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Bolc, Leonard. Computational Models of Learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987.

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Computational models of games. Cambridge, Mass: MIT Press, 1989.

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Computational models of conditioning. New York: Cambridge University Press, 2010.

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Raman, Indhumathi, Poonthalir Ganesan, Venkatasamy Sureshkumar, and Latha Ranganathan, eds. Computational Intelligence, Cyber Security and Computational Models. Recent Trends in Computational Models, Intelligent and Secure Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15556-7.

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Källén, Anders. Computational pharmacokinetics. Boca Raton: Taylor & Francis, 2007.

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Book chapters on the topic "Computational models"

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Steele, Guy L., Xiaowei Shen, Josep Torrellas, Mark Tuckerman, Eric J. Bohm, Laxmikant V. Kalé, Glenn Martyna, et al. "Computational Models." In Encyclopedia of Parallel Computing, 352. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-09766-4_2267.

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Silva, Ana, Jorge de Brito, and Pedro Lima Gaspar. "Computational Models." In Green Energy and Technology, 219–62. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33290-1_5.

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van Gils, Stephan, and Wim van Drongelen. "Epilepsy: Computational Models." In Encyclopedia of Computational Neuroscience, 1121–34. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-6675-8_504.

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Akerkar, Rajendra. "Assorted Computational Models." In Advanced Information and Knowledge Processing, 85–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91851-8_4.

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Goriely, Alain. "Discrete Computational Models." In Interdisciplinary Applied Mathematics, 51–59. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-0-387-87710-5_3.

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Uspensky, Vladimir, and Alexei Semenov. "Convenient computational models." In Algorithms: Main Ideas and Applications, 115–17. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8232-2_21.

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Uspensky, Vladimir, and Alexei Semenov. "Representative computational models." In Algorithms: Main Ideas and Applications, 22–30. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8232-2_5.

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Liu, Xin, Anwitaman Datta, and Karl Aberer. "Computational Trust Models." In Encyclopedia of Social Network Analysis and Mining, 1–11. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4614-7163-9_228-1.

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van Gils, Stephan, and Wim van Drongelen. "Epilepsy: Computational Models." In Encyclopedia of Computational Neuroscience, 1–17. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7320-6_504-1.

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Soni, Bharat K., Jong-Eun Kim, Yasushi Ito, Christina D. Wagner, and King-Hay Yang. "Pediatric Computational Models." In Pediatric Injury Biomechanics, 287–334. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4154-0_7.

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Conference papers on the topic "Computational models"

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Garrido, José M. "Developing computational models." In the 51st ACM Southeast Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2498328.2500055.

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Szabó, Gábor. "Computational Models for Morphology." In MultiScience - XXXI. microCAD International Multidisciplinary Scientific Conference. University of Miskolc, 2017. http://dx.doi.org/10.26649/musci.2017.059.

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Bagherzadeh, Nader. "Session details: Computational models." In CF04: Computing Frontiers Conference. New York, NY, USA: ACM, 2004. http://dx.doi.org/10.1145/3244170.

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Oakes, Bentley James, Romain Franceschini, Simon Van Mierlo, and Hans Vangheluwe. "The Computational Notebook Paradigm for Multi-paradigm Modeling." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00072.

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Guven, Cicek, Mike Holenderski, Tanir Ozcelebi, and Johan Lukkien. "A formalization of computational trust." In 2017 Internet of Things - Business Models, Users, and Networks. IEEE, 2017. http://dx.doi.org/10.1109/ctte.2017.8260936.

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"Tutorial T1B: Emerging Computational Devices, Architectures and Computational Models." In 2018 31st International Conference on VLSI Design and 2018 17th International Conference on Embedded Systems (VLSID). IEEE, 2018. http://dx.doi.org/10.1109/vlsid.2018.18.

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Rodriguez, Luis-Felipe, Felix Ramos, and Yingxu Wang. "Cognitive computational models of emotions." In Cognitive Computing (ICCI-CC). IEEE, 2011. http://dx.doi.org/10.1109/coginf.2011.6016124.

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Kelly, Ashley R., Allan McDougall, and Nike Abbott. "Rhetorical models for computational systems." In the 27th ACM international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1621995.1622025.

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Chen, Xue-wen. "Computational models in systems biology." In 2009 IEEE International Conference on Granular Computing (GRC). IEEE, 2009. http://dx.doi.org/10.1109/grc.2009.5255139.

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Polatsek, Patrik, Marek Jakab, Wanda Benesova, and Matej Kužma. "Computational models of shape saliency." In Eleventh International Conference on Machine Vision, edited by Dmitry P. Nikolaev, Petia Radeva, Antanas Verikas, and Jianhong Zhou. SPIE, 2019. http://dx.doi.org/10.1117/12.2522779.

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Reports on the topic "Computational models"

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Brown, Joshua W. Computational Neural Models of Risk. Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada515423.

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Dietterich, Thomas G., and Prasad Tadepalli. Hybrid Computational Models for Skill Acquisition. Fort Belvoir, VA: Defense Technical Information Center, August 1998. http://dx.doi.org/10.21236/ada353324.

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Hegemier, Gilbert. Advanced Computational Models for Fabric-Reinforced Composites. Fort Belvoir, VA: Defense Technical Information Center, October 2001. http://dx.doi.org/10.21236/ada397336.

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Resasco, Diana C., and Martin H. Schultz. High Performance Computer Models in Computational Acoustics. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada628567.

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Letendre, Kenneth, and Robert G. Abbott. Computational models of intergroup competition and warfare. Office of Scientific and Technical Information (OSTI), November 2011. http://dx.doi.org/10.2172/1034876.

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Whitcomb, Timothy R., and Alan J. Wallcraft. ESPC Computational Efficiency of Earth System Models. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada616657.

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Hewett, D. W. Simulation models for computational plasma physics: Concluding report. Office of Scientific and Technical Information (OSTI), March 1994. http://dx.doi.org/10.2172/10142303.

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Cook, Chris B., and Marshall C. Richmond. Simulation of Tailrace Hydrodynamics Using Computational Fluid Dynamics Models. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/789270.

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Riesenhuber, Maximilian, and Tomaso Poggio. Computational Models of Object Recognition in Cortex: A Review. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada458109.

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Cook, Christopher B., and Marshall C. Richmond. Simulation of Tailrace Hydrodynamics Using Computational Fluid Dynamics Models. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/965659.

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