Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited-Reference-Cited by-同舟云学术

Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited

Published:2018-12-05 Issue:3 Volume:15 Page:1546-1559
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Zaspel Peter¹,Huang Bing²,Harbrecht Helmut¹,von Lilienfeld O. Anatole²^ORCID

Affiliation:

1. Department of Mathematics and Computer Science, University of Basel, Spiegelgasse 1, 4051 Basel, Switzerland

2. Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials (MARVEL), Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel, Switzerland

Funder

Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.8b00832

Reference101 articles.

1. Chemical space

2. The drug-maker's guide to the galaxy

3. Predicting Properties from Scratch

4. Toward Computational Materials Design: The Impact of Density Functional Theory on Materials Research

5. von Lilienfeld, O. A. In Many-Electron Approaches in Physics, Chemistry and Mathematics; Bach, V., Site, L. D., Eds.; Mathematical Physics Studies; Springer, 2014; Vol. IX, p 417.

Cited by 78 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integration of artificial intelligence and big data in materials science: New paradigms and scientific discoveries;Chinese Science Bulletin;2024-07-01

2. Thermal conductivity of Li3PS4 solid electrolytes with ab initio accuracy;Physical Review Materials;2024-06-12

3. Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications;Physical Review Applied;2024-06-04

4. Reducing training data needs with minimal multilevel machine learning (M3L);Machine Learning: Science and Technology;2024-06-01

5. In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back;Advanced Materials;2024-05-25