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pro vyhledávání: '"Hugh M Cartwright"'
Autor:
Hugh M. Cartwright
In recent years, interest in applying Artificial Intelligence to scientific problems has grown rapidly. There is a danger, however, that, in one's enthusiasm for the new methods, potential challenges might be overlooked. This chapter covers some of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c846ef1db7a215d42cca8e4c675d746a
https://doi.org/10.1039/9781839160233-00109
https://doi.org/10.1039/9781839160233-00109
Publikováno v:
Butler, K T, Davies, D W, Cartwright, H, Isayev, O & Walsh, A 2018, ' Machine learning for molecular and materials science ', Nature, vol. 559, no. 7715, pp. 547-555 . https://doi.org/10.1038/s41586-018-0337-2
Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a futu
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae3b976343045821dd25b0583d944829
https://doi.org/10.1038/s41586-018-0337-2
https://doi.org/10.1038/s41586-018-0337-2
Autor:
Hugh M Cartwright
Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show
Autor:
Hugh M. Cartwright
Publikováno v:
Methods in Molecular Biology™ ISBN: 9781588297181
Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical scienc
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https://ora.ox.ac.uk/objects/uuid:d4ae695e-15e5-4a03-9896-e991ae30b0e9
https://ora.ox.ac.uk/objects/uuid:d4ae695e-15e5-4a03-9896-e991ae30b0e9
Autor:
Walter J. Balfour, Hugh M. Cartwright
A new 2 Σ + -X 2 Σ + transition in MgH has been found in emission. The upper state of this system lies lower in energy than any of the previously identified excited 2 Σ + states of MgH. The 2 Σ + state is relatively weakly bound at large internuc
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https://ora.ox.ac.uk/objects/uuid:9e2c1d9d-aac2-48b8-8ad8-a53cefef336d
https://ora.ox.ac.uk/objects/uuid:9e2c1d9d-aac2-48b8-8ad8-a53cefef336d
Autor:
Hugh M. Cartwright
It is often necessary in science to identify samples that have features in common. For example, one might wish to find those NMR spectra in a large database that have similar patterns of resonances or identify samples amongst a large number of specim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67d0c83a41aa01bea5e8f05f89388623
https://ora.ox.ac.uk/objects/uuid:c5009c6a-979a-4bc3-b859-4b986399ab7f
https://ora.ox.ac.uk/objects/uuid:c5009c6a-979a-4bc3-b859-4b986399ab7f
Autor:
Silvia Curteanu, Hugh M. Cartwright
Publikováno v:
Journal of Chemometrics. 25:527-549
Artificial neural networks (ANNs) are comparatively straightforward to understand and use in the analysis of scientific data. However, this relative transparency may encourage their use in an uncritical, and therefore possibly unproductive, fashion.
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https://explore.openaire.eu/search/publication?articleId=doi_________::83c5f57a233171f3f10c157167529167
https://doi.org/10.1002/cem.1401
https://doi.org/10.1002/cem.1401
Autor:
Hugh M. Cartwright
Publikováno v:
Methods in Molecular Biology ISBN: 9781493922383
Artificial Neural Networks
Artificial Neural Networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56a3e59a55175fc7100c3dc09138a336
https://doi.org/10.1007/978-1-4939-2239-0
https://doi.org/10.1007/978-1-4939-2239-0