ExLibris header image
SFX Logo
Title: Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond
Source:

Journal of Chemical Physics [0021-9606] yr:2014


Collapse list of basic services Basic
Full text
Full text available via AIP Journals (American Institute of Physics)
GO
Document delivery
Request document via Library/Bibliothek GO
Users interested in this article also expressed an interest in the following:
1. Mitchell, M. I. M. "Machine learning: Trends, perspectives, and prospects." Science 349.6245 (2015): 255-260. Link to SFX for this item
2. Albayda, J. "Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods." PLoS One 12.8 (2017). Link to Full Text for this item Link to SFX for this item
3. Carrasquilla, J. "Machine learning phases of matter." Nature physics. 13.5: 431-434. Link to SFX for this item
4. Devaul, Holly D. "Computer-assisted assignment of educational standards using natural language processing." Journal of the American Society for Information Science and Technology 62.2 (2011): 395-405. Link to Full Text for this item Link to SFX for this item
5. Sajda, P. "Machine learning for detection and diagnosis of disease." Annual review of biomedical engineering 8.1 (2006): 537-65. Link to Full Text for this item Link to SFX for this item
6. Ghahramani, Z. "Probabilistic machine learning and artificial intelligence." Nature 521.7553 (2015): 452-9. Link to Full Text for this item Link to SFX for this item
7. Brynjolfsson, E. "What can machine learning do? Workforce implications." Science 358.6370 (2017): 1530-1534. Link to SFX for this item
8. LeCun, Y. "Deep learning." Nature 521.7553 (2015): 436-444. Link to Full Text for this item Link to SFX for this item
9. Grimmer, J. "We Are All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together." PS, political science & politics 48.1 (2015): 80-83. Link to SFX for this item
10. Domingos, P. "A Few Useful Things to Know About Machine Learning." Communications of the ACM 55.10 (2012): 78-87. Link to SFX for this item
11. Chahal, A. "Machine Learning and Deep Learning." International Journal of Innovative Technology and Exploring Engineering 8.12 (2019): 4910-4914. Link to SFX for this item
12. Saeys, Y. "A review of feature selection techniques in bioinformatics." Bioinformatics 23.19 (2007): 2507-2517. Link to Full Text for this item Link to SFX for this item
13. Wick, C. "Deep Learning." Informatik-Spektrum 40.1 (2016): 1-5. Link to Full Text for this item Link to SFX for this item
14. Wysotzki, F. "Maschinelles Lernen." at - Automatisierungstechnik 45.11 (1997): 526-536. Link to SFX for this item
15. Lan, H. "DLPlib: A Library for Deep Learning Processor." Journal of computer science and technology 32.2: 286-296. Link to SFX for this item
16. Herdman, P.-N. M. "Entanglement area law in superfluid 4He." Nature Physics advance on.6 (2017): 556-558. Link to SFX for this item
17. Hush, Michael R. "Machine learning for quantum physics." Science 355.6325 (2017): 580-580. Link to SFX for this item
18. Limburg, A. Schreiben in den Wirtschaftswissenschaften. 2011. Link to SFX for this item
19. Krakauer, D. "The challenges and scope of theoretical biology." Journal of theoretical biology 276.1 (2011): 269-276. Link to SFX for this item
20. Stewart, C. "Whither Metrics? Tools for Assessing Publication Impact of Academic Library Practitioners." Journal of academic librarianship 36.5 (2010): 449-453. Link to SFX for this item
View More...
View Less...
Select All Clear All

Expand list of advanced services Advanced
A service provided by the Library of the Wissenschaftspark Albert Einstein, Potsdam, Germany.
© 2005 SFX by Ex Libris Inc.