DOI: 10.1021/acs.jctc.7b00577. Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

10.1021/acs.jctc.7b00577

Crossref journal-article

American Chemical Society (ACS)

Journal of Chemical Theory and Computation (316)

Bibliography

Faber, F. A., Hutchison, L., Huang, B., Gilmer, J., Schoenholz, S. S., Dahl, G. E., Vinyals, O., Kearnes, S., Riley, P. F., & von Lilienfeld, O. A. (2017). Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error. Journal of Chemical Theory and Computation, 13(11), 5255â5264.

Authors 10

Felix A. Faber (first)
Luke Hutchison (additional)
Bing Huang (additional)
Justin Gilmer (additional)
Samuel S. Schoenholz (additional)
George E. Dahl (additional)
Oriol Vinyals (additional)
Steven Kearnes (additional)
Patrick F. Riley (additional)
O. Anatole von Lilienfeld (additional)

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Dates

Type	When
Created	7 years, 11 months ago (Sept. 19, 2017, 2:07 p.m.)
Deposited	2 years, 3 months ago (April 25, 2023, 11:51 p.m.)
Indexed	1 day, 8 hours ago (Aug. 23, 2025, 9:37 p.m.)
Issued	7 years, 10 months ago (Oct. 10, 2017)
Published	7 years, 10 months ago (Oct. 10, 2017)
Published Online	7 years, 10 months ago (Oct. 10, 2017)
Published Print	7 years, 9 months ago (Nov. 14, 2017)

Funders 4

Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung 10.13039/501100001711 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Region: Europe
pri (Trusts, charities, foundations (both public and private))
Labels10
1. Schweizerischer Nationalfonds
2. Swiss National Science Foundation
3. Fonds National Suisse de la Recherche Scientifique
4. Fondo Nazionale Svizzero per la Ricerca Scientifica
5. Fonds National Suisse
6. Fondo Nazionale Svizzero
7. Schweizerische Nationalfonds
8. SNF
9. SNSF
10. FNS
Awards2
1. 310030_160067
2. PP00P2_138932
Air Force Office of Scientific Research 10.13039/100000181
Region: Americas
gov (National government)
Labels4
1. AF Office of Scientific Research
2. US Air Force Office of Scientific Research
3. United States Air Force Office of Scientific Research
4. AFOSR
Awards1
1. FA9550-15-1-0026
Google 10.13039/100006785
Region: Americas
gov (For-profit companies (industry))
Labels2
1. Google LLC
2. Google Inc.
Forschungsfonds, Universit?t Basel

BibTeX

@article{Faber_2017, title={Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error}, volume={13}, ISSN={1549-9626}, url={http://dx.doi.org/10.1021/acs.jctc.7b00577}, DOI={10.1021/acs.jctc.7b00577}, number={11}, journal={Journal of Chemical Theory and Computation}, publisher={American Chemical Society (ACS)}, author={Faber, Felix A. and Hutchison, Luke and Huang, Bing and Gilmer, Justin and Schoenholz, Samuel S. and Dahl, George E. and Vinyals, Oriol and Kearnes, Steven and Riley, Patrick F. and von Lilienfeld, O. Anatole}, year={2017}, month=oct, pages={5255–5264} }

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