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Artykuły w czasopismach na temat „Computational perspective”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 20 lutego 2023

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1

Rosenberg, Ari, Jaclyn Sky Patterson i Dora E. Angelaki. "A computational perspective on autism". Proceedings of the National Academy of Sciences 112, nr 30 (13.07.2015): 9158–65. http://dx.doi.org/10.1073/pnas.1510583112.

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Autism is a neurodevelopmental disorder that manifests as a heterogeneous set of social, cognitive, motor, and perceptual symptoms. This system-wide pervasiveness suggests that, rather than narrowly impacting individual systems such as affection or vision, autism may broadly alter neural computation. Here, we propose that alterations in nonlinear, canonical computations occurring throughout the brain may underlie the behavioral characteristics of autism. One such computation, called divisive normalization, balances a neuron’s net excitation with inhibition reflecting the overall activity of the neuronal population. Through neural network simulations, we investigate how alterations in divisive normalization may give rise to autism symptomatology. Our findings show that a reduction in the amount of inhibition that occurs through divisive normalization can account for perceptual consequences of autism, consistent with the hypothesis of an increased ratio of neural excitation to inhibition (E/I) in the disorder. These results thus establish a bridge between an E/I imbalance and behavioral data on autism that is currently absent. Interestingly, our findings implicate the context-dependent, neuronal milieu as a key factor in autism symptomatology, with autism reflecting a less “social” neuronal population. Through a broader discussion of perceptual data, we further examine how altered divisive normalization may contribute to a wide array of the disorder’s behavioral consequences. These analyses show how a computational framework can provide insights into the neural basis of autism and facilitate the generation of falsifiable hypotheses. A computational perspective on autism may help resolve debates within the field and aid in identifying physiological pathways to target in the treatment of the disorder.

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2

Shi, Shaolong, Neda Sharifi, U. Kei Cheang i Yifan Chen. "Perspective: Computational Nanobiosensing". IEEE Transactions on NanoBioscience 19, nr 2 (kwiecień 2020): 267–69. http://dx.doi.org/10.1109/tnb.2019.2956470.

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BENTON, P. N., G. M. BIERMAN i V. C. V. DE PAIVA. "Computational types from a logical perspective". Journal of Functional Programming 8, nr 2 (marzec 1998): 177–93. http://dx.doi.org/10.1017/s0956796898002998.

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Moggi's computational lambda calculus is a metalanguage for denotational semantics which arose from the observation that many different notions of computation have the categorical structure of a strong monad on a cartesian closed category. In this paper we show that the computational lambda calculus also arises naturally as the term calculus corresponding (by the Curry–Howard correspondence) to a novel intuitionistic modal propositional logic. We give natural deduction, sequent calculus and Hilbert-style presentations of this logic and prove strong normalisation and confluence results.

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4

Stoneham, A. M. "Computational physics: a perspective". Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 360, nr 1795 (23.04.2002): 1107–21. http://dx.doi.org/10.1098/rsta.2002.0985.

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Almeida, Antônio-Carlos Guimarães de, Antônio Márcio Rodrigues i Antonio Fernando Catelli Infantosi. "Computational neuroscience in perspective". Revista Brasileira de Engenharia Biomédica 30, nr 3 (wrzesień 2014): 205–6. http://dx.doi.org/10.1590/1517-3151.3003.

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Veale, Tony, Ekaterina Shutova i Beata Beigman Klebanov. "Metaphor: A Computational Perspective". Synthesis Lectures on Human Language Technologies 9, nr 1 (29.02.2016): 1–160. http://dx.doi.org/10.2200/s00694ed1v01y201601hlt031.

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Strapparava, Carlo. "Metaphor: A Computational Perspective". Computational Linguistics 44, nr 1 (marzec 2018): 191–92. http://dx.doi.org/10.1162/coli_r_00311.

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8

Magnani, Lorenzo. "Conceptualizing Machines in an Eco-Cognitive Perspective". Philosophies 7, nr 5 (25.08.2022): 94. http://dx.doi.org/10.3390/philosophies7050094.

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Eco-cognitive computationalism explores computing in context, adhering to some of the key ideas presented by modern cognitive science perspectives on embodied, situated, and distributed cognition. First of all, when physical computation is seen from the perspective of the ecology of cognition it is possible to clearly understand the role Turing assigned to the process of “education” of the machine, paralleling it to the education of human brains, in the invention of the Logical Universal Machine. It is this Turing’s emphasis on education that furnishes the justification of the conceptualization of machines as “domesticated ignorant entities”, that is proposed in this article. I will show that conceptualizing machines as dynamically active in distributed physical entities of various kinds suitably transformed so that data can be encoded and decoded to obtain appropriate results sheds further light on my eco-cognitive perspective. Furthermore, it is within this intellectual framework that I will usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities thanks to morphological features: ignorant bodies can be computationally domesticated to make an intertwined computation simpler, relying on the “simplexity” of animal embodied cognition, which represents one of the main qualities of organic agents. Finally, eco-cognitive computationalism allows us to clearly acknowledge that the concept of computation evolves over time as a result of historical and contextual factors, and we can construct an epistemological view that depicts the “emergence” of new types of computations that exploit new substrates. This new viewpoint demonstrates how the computational domestication of ignorant entities might result in the emergence of novel unconventional cognitive embodiments.

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9

Ciliberto, Carlo, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini i Leonard Wossnig. "Quantum machine learning: a classical perspective". Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 474, nr 2209 (styczeń 2018): 20170551. http://dx.doi.org/10.1098/rspa.2017.0551.

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Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed.

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10

Johnson, Austin. "Computational linguistics and temporal perspective". Journal of Research Design and Statistics in Linguistics and Communication Science 3, nr 2 (7.12.2016): 251–67. http://dx.doi.org/10.1558/jrds.30022.

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11

Forbes, Tony, Richard Crandall i Carl Pomerance. "Prime Numbers: A Computational Perspective". Mathematical Gazette 86, nr 507 (listopad 2002): 552. http://dx.doi.org/10.2307/3621190.

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12

Langberg, Michael, Alexander Sprintson i Jehoshua Bruck. "Network Coding: A Computational Perspective". IEEE Transactions on Information Theory 55, nr 1 (styczeń 2009): 147–57. http://dx.doi.org/10.1109/tit.2008.2008135.

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13

Kong, Yong, i Jin-Hua Han. "MicroRNA: Biological and Computational Perspective". Genomics, Proteomics & Bioinformatics 3, nr 2 (2005): 62–72. http://dx.doi.org/10.1016/s1672-0229(05)03011-1.

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14

Veale, Tony, Pablo Gervás i Alison Pease. "Understanding creativity: A computational perspective". New Generation Computing 24, nr 3 (wrzesień 2006): 203–7. http://dx.doi.org/10.1007/bf03037331.

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15

Bajorath, Jürgen. "A Perspective on Computational Chemogenomics". Molecular Informatics 32, nr 11-12 (1.07.2013): 1025–28. http://dx.doi.org/10.1002/minf.201300034.

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16

Stuart, A. M. "Inverse problems: A Bayesian perspective". Acta Numerica 19 (maj 2010): 451–559. http://dx.doi.org/10.1017/s0962492910000061.

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The subject of inverse problems in differential equations is of enormous practical importance, and has also generated substantial mathematical and computational innovation. Typically some form of regularization is required to ameliorate ill-posed behaviour. In this article we review the Bayesian approach to regularization, developing a function space viewpoint on the subject. This approach allows for a full characterization of all possible solutions, and their relative probabilities, whilst simultaneously forcing significant modelling issues to be addressed in a clear and precise fashion. Although expensive to implement, this approach is starting to lie within the range of the available computational resources in many application areas. It also allows for the quantification of uncertainty and risk, something which is increasingly demanded by these applications. Furthermore, the approach is conceptually important for the understanding of simpler, computationally expedient approaches to inverse problems.

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17

Qin, Mingpu, Thomas Schäfer, Sabine Andergassen, Philippe Corboz i Emanuel Gull. "The Hubbard Model: A Computational Perspective". Annual Review of Condensed Matter Physics 13, nr 1 (10.03.2022): 275–302. http://dx.doi.org/10.1146/annurev-conmatphys-090921-033948.

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The Hubbard model is the simplest model of interacting fermions on a lattice and is of similar importance to correlated electron physics as the Ising model is to statistical mechanics or the fruit fly to biomedical science. Despite its simplicity, the model exhibits an incredible wealth of phases, phase transitions, and exotic correlation phenomena. Although analytical methods have provided a qualitative description of the model in certain limits, numerical tools have shown impressive progress in achieving quantitative accurate results over the past several years. This article gives an introduction to the model, motivates common questions, and illustrates the progress that has been achieved over recent years in revealing various aspects of the correlation physics of the model.

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18

Kleine, Liliana López. "Computational Biology: a Statistical Mechanics Perspective". Journal of the Royal Statistical Society: Series A (Statistics in Society) 173, nr 2 (kwiecień 2010): 462–63. http://dx.doi.org/10.1111/j.1467-985x.2009.00634_3.x.

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19

Shekhar, Shashi, Zhe Jiang, Reem Ali, Emre Eftelioglu, Xun Tang, Venkata Gunturi i Xun Zhou. "Spatiotemporal Data Mining: A Computational Perspective". ISPRS International Journal of Geo-Information 4, nr 4 (28.10.2015): 2306–38. http://dx.doi.org/10.3390/ijgi4042306.

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Marvin, Joseph G. "Perspective on computational fluid dynamics validation". AIAA Journal 33, nr 10 (październik 1995): 1778–87. http://dx.doi.org/10.2514/3.12727.

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21

Rothermich, Joe. "A perspective on computational intelligence education". IEEE Computational Intelligence Magazine 4, nr 2 (maj 2009): 50–51. http://dx.doi.org/10.1109/mci.2009.932256.

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22

Sosa, Ricardo, i John S. Gero. "Multi-dimensional creativity: a computational perspective". International Journal of Design Creativity and Innovation 4, nr 1 (7.04.2015): 26–50. http://dx.doi.org/10.1080/21650349.2015.1026941.

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23

Beerenwinkel, Niko, Chris D. Greenman i Jens Lagergren. "Computational Cancer Biology: An Evolutionary Perspective". PLOS Computational Biology 12, nr 2 (4.02.2016): e1004717. http://dx.doi.org/10.1371/journal.pcbi.1004717.

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24

Dahlem, M. A., i E. P. Chronicle. "A computational perspective on migraine aura". Progress in Neurobiology 74, nr 6 (grudzień 2004): 351–61. http://dx.doi.org/10.1016/j.pneurobio.2004.10.003.

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25

Clark, James E., Stuart Watson i Karl J. Friston. "What is mood? A computational perspective". Psychological Medicine 48, nr 14 (26.02.2018): 2277–84. http://dx.doi.org/10.1017/s0033291718000430.

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AbstractThe neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of – or certainty about – the predicted sensorimotor/interoceptive consequences of action. By extending this reasoning, in a hierarchical setting, we suggest mood states act as (hyper) priors over uncertainty (i.e. emotions). Here, we consider the same computational pathology in the proprioceptive and interoceptive (behavioural and autonomic) domain in order to furnish an explanation for mood disorders. This formulation reconciles several strands of research at multiple levels of enquiry.

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26

Cuppen, H. M., A. Fredon, T. Lamberts, E. M. Penteado, M. Simons i C. Walsh. "Surface astrochemistry: a computational chemistry perspective". Proceedings of the International Astronomical Union 13, S332 (marzec 2017): 293–304. http://dx.doi.org/10.1017/s1743921317009929.

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AbstractMolecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. Especially, saturated, hydrogen-rich molecules are formed through surface chemistry. Astrochemical models have developed over the decades to understand the molecular processes in the interstellar medium, taking into account grain surface chemistry. However, essential input information for gas-grain models, such as binding energies of molecules to the surface, have been derived experimentally only for a handful of species, leaving hundreds of species with highly uncertain estimates. Moreover, some fundamental processes are not well enough constrained to implement these into the models.The proceedings gives three examples how computational chemistry techniques can help answer fundamental questions regarding grain surface chemistry.

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27

Larson, Richard B. "Historical Perspective on Computational Star Formation". Proceedings of the International Astronomical Union 6, S270 (maj 2010): 1–5. http://dx.doi.org/10.1017/s1743921311000093.

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The idea that stars are formed by gravity goes back more than 300 years to Newton, and the idea that gravitational instability plays a role goes back more than 100 years to Jeans, but the idea that stars are forming at the present time in the interstellar medium is more recent and did not emerge until the energy source of stars had been identified and it was realized that the most luminous stars have short lifetimes and therefore must have formed recently. The first suggestion that stars may be forming now in the interstellar medium was credited by contemporary authors to a paper by Spitzer in 1941 in which he talks about the formation of interstellar condensations by radiation pressure, but then oddly says nothing about star formation. That may be because, as Spitzer later told me, when he first suggested very tentatively in a paper submitted to The Astrophysical Journal that stars might be forming now from interstellar matter, this was considered a radical idea and the referee said it was much too speculative and should be taken out of the paper. So Spitzer removed the speculation about star formation from the published version of his paper.

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28

Dunnett, Stephen B. "A computational perspective on the striatum". Trends in Neurosciences 24, nr 11 (listopad 2001): 675. http://dx.doi.org/10.1016/s0166-2236(00)01962-7.

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Mahfouz, Ahmed, Sjoerd M. H. Huisman, Boudewijn P. F. Lelieveldt i Marcel J. T. Reinders. "Brain transcriptome atlases: a computational perspective". Brain Structure and Function 222, nr 4 (1.12.2016): 1557–80. http://dx.doi.org/10.1007/s00429-016-1338-2.

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Yue, Dong, Jia Meng, Mingzhu Lu, C. L. Chen, Maozu Guo i Yufei Huang. "Understanding MicroRNA Regulation: A computational perspective". IEEE Signal Processing Magazine 29, nr 1 (styczeń 2012): 77–88. http://dx.doi.org/10.1109/msp.2011.943013.

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Frank, M. J. "Schizophrenia: A Computational Reinforcement Learning Perspective". Schizophrenia Bulletin 34, nr 6 (20.08.2008): 1008–11. http://dx.doi.org/10.1093/schbul/sbn123.

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32

Noor, A. K., i S. L. Venneri. "A perspective on computational structures technology". Computer 26, nr 10 (październik 1993): 38–46. http://dx.doi.org/10.1109/2.237442.

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Guo, Qin, Mingxing Luo, Lixiang Li i Yixian Yang. "A Computational Perspective on Network Coding". Mathematical Problems in Engineering 2010 (2010): 1–11. http://dx.doi.org/10.1155/2010/436354.

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From the perspectives of graph theory and combinatorics theory we obtain some new upper bounds on the number of encoding nodes, which can characterize the coding complexity of the network coding, both in feasible acyclic and cyclic multicast networks. In contrast to previous work, during our analysis we first investigate the simple multicast network with source rateh=2, and thenh≥2. We find that for feasible acyclic multicast networks our upper bound is exactly the lower bound given by M. Langberg et al. in 2006. So the gap between their lower and upper bounds for feasible acyclic multicast networks does not exist. Based on the new upper bound, we improve the computational complexity given by M. Langberg et al. in 2009. Moreover, these results further support the feasibility of signatures for network coding.

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34

Hobert, James P. "Hierarchical Models: A Current Computational Perspective". Journal of the American Statistical Association 95, nr 452 (grudzień 2000): 1312–16. http://dx.doi.org/10.1080/01621459.2000.10474338.

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Yaşar, Osman. "A new perspective on computational thinking". Communications of the ACM 61, nr 7 (25.06.2018): 33–39. http://dx.doi.org/10.1145/3214354.

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Nachman, Arje. "A Brief Perspective on Computational Electromagnetics". Journal of Computational Physics 126, nr 1 (czerwiec 1996): 237–39. http://dx.doi.org/10.1006/jcph.1996.0132.

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37

Bhaskar, Harish, i Sameer Singh. "Live cell imaging: a computational perspective". Journal of Real-Time Image Processing 1, nr 3 (20.03.2007): 195–212. http://dx.doi.org/10.1007/s11554-007-0022-4.

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Chumbley, Justin, i Annekatrin Steinhoff. "A computational perspective on social attachment". Infant Behavior and Development 54 (luty 2019): 85–98. http://dx.doi.org/10.1016/j.infbeh.2018.12.001.

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Roughgarden, Tim. "Computing equilibria: a computational complexity perspective". Economic Theory 42, nr 1 (27.02.2009): 193–236. http://dx.doi.org/10.1007/s00199-009-0448-y.

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Macías-ramos, Luis F., Bosheng Song, Luis Valencia-Cabrera, Linqiang Pan i Mario J. Pérez-jiménez. "Membrane fission: A computational complexity perspective". Complexity 21, nr 6 (27.04.2015): 321–34. http://dx.doi.org/10.1002/cplx.21691.

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Ceballos, Manuel, Juan Núñez i Ángel F. Tenorio. "Computing abelian subalgebras for linear algebras of upper-triangular matrices from an algorithmic perspective". Analele Universitatii "Ovidius" Constanta - Seria Matematica 24, nr 2 (1.06.2016): 137–47. http://dx.doi.org/10.1515/auom-2016-0032.

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Abstract In this paper, the maximal abelian dimension is algorithmically and computationally studied for the Lie algebra hn, of n×n upper-triangular matrices. More concretely, we define an algorithm to compute abelian subalgebras of hn besides programming its implementation with the symbolic computation package MAPLE. The algorithm returns a maximal abelian subalgebra of hn and, hence, its maximal abelian dimension. The order n of the matrices hn is the unique input needed to obtain these subalgebras. Finally, a computational study of the algorithm is presented and we explain and comment some suggestions and comments related to how it works.

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42

Cohen, Stanley, Bhagavathi Ramamurthy i FrederickD Coffman. "A perspective on digital and computational pathology". Journal of Pathology Informatics 6, nr 1 (2015): 29. http://dx.doi.org/10.4103/2153-3539.158059.

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Zhuang, Yue-ting. "Data-driven digital entertainment: a computational perspective". Journal of Zhejiang University SCIENCE C 14, nr 7 (lipiec 2013): 475–76. http://dx.doi.org/10.1631/jzus.cide1300.

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Kahn, Ken. "A half-century perspective on computational thinking". Tecnologias, Sociedade e Conhecimento 4, nr 1 (20.12.2021): 23–42. http://dx.doi.org/10.20396/tsc.v4i1.14483.

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Há mais de cinquenta anos que as pessoas exploram como os computadores podem melhorar a aprendizagem e o ensino. A natureza maleável dos computadores permitiu que ele funcione como cartão de memória, tutor pessoal, livro didático, livro de referência, laboratório virtual, questionário, espaço virtual, sala de conferências e grupos de estudo. Talvez a sugestão mais radical seja conceber o computador como algo que aprendizes podem moldar de forma criativa resultando em algo realmente significativo, dinâmico, interativo e compartilhado. E, ainda, que o processo de construção desses artefatos computacionais seja rico em oportunidades de aprendizagem. Estas oportunidades variam desde ganhar uma compreensão mais profunda do assunto até a construir habilidades de alto nível de pensamento e de resolução de problemas.

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45

Teitelbaum, Jeremy. "Book Review: Prime numbers: A computational perspective". Bulletin of the American Mathematical Society 39, nr 03 (15.04.2002): 449–55. http://dx.doi.org/10.1090/s0273-0979-02-00947-3.

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Hunt, Patricia A. "Organolanthanide mediated catalytic cycles: a computational perspective". Dalton Transactions, nr 18 (2007): 1743. http://dx.doi.org/10.1039/b700876g.

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Roman, T., W. A. Diño, H. Nakanishi i H. Kasai. "High-uptake graphene hydrogenation: a computational perspective". Journal of Physics: Condensed Matter 21, nr 47 (5.11.2009): 474219. http://dx.doi.org/10.1088/0953-8984/21/47/474219.

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48

Bungartz, Hans-Joachim, Donald Estep, Ulrich Rüde i Peter Turner. "Computational Science and Engineering Education: SIAM's Perspective". Computing in Science & Engineering 11, nr 6 (listopad 2009): 5–11. http://dx.doi.org/10.1109/mcse.2009.189.

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Palazzo, Teresa A., i Karl Anker Jørgensen. "Higher-order cycloaddition reactions: A computational perspective". Tetrahedron 74, nr 52 (grudzień 2018): 7381–87. http://dx.doi.org/10.1016/j.tet.2018.11.008.

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Yuille, Alan. "An information theory perspective on computational vision". Frontiers of Electrical and Electronic Engineering in China 5, nr 3 (5.08.2010): 329–46. http://dx.doi.org/10.1007/s11460-010-0107-x.

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