Materials and Megabytes

O. Anatole von Lilienfeld (Season 2, Ep. 2)

January 25, 2019 Gowoon Cheon / O. Anatole von Lilienfeld Season 2 Episode 2
Materials and Megabytes
O. Anatole von Lilienfeld (Season 2, Ep. 2)
Chapters
Materials and Megabytes
O. Anatole von Lilienfeld (Season 2, Ep. 2)
Jan 25, 2019 Season 2 Episode 2
Gowoon Cheon / O. Anatole von Lilienfeld

Our guest for this episode is Prof. Dr. O. Anatole von Lilienfeld from the University of Basel.

Some relevant papers:

  • Huang, B., and von Lilienfeld, O. A., The ‘DNA’ of Chemistry: Scalable Quantum Machine Learning with ‘Amons.’ arXiv:1707.04146, (2017)
  • Ramakrishnan, R., Dral, P. O., Rupp, M., and von Lilienfeld, O. A., Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. Journal of Chemical Theory and Computation, doi:10.1021/acs.jctc.5b00099 (2015)
  • Rupp, M., Tkatchenko, A., Müller, K.-R., and von Lilienfeld, O. A., Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning. Physical Review Letters, doi:10.1103/PhysRevLett.108.058301 (2012)


Group website: https://www.chemie.unibas.ch/~anatole/

Show Notes

Our guest for this episode is Prof. Dr. O. Anatole von Lilienfeld from the University of Basel.

Some relevant papers:

  • Huang, B., and von Lilienfeld, O. A., The ‘DNA’ of Chemistry: Scalable Quantum Machine Learning with ‘Amons.’ arXiv:1707.04146, (2017)
  • Ramakrishnan, R., Dral, P. O., Rupp, M., and von Lilienfeld, O. A., Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. Journal of Chemical Theory and Computation, doi:10.1021/acs.jctc.5b00099 (2015)
  • Rupp, M., Tkatchenko, A., Müller, K.-R., and von Lilienfeld, O. A., Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning. Physical Review Letters, doi:10.1103/PhysRevLett.108.058301 (2012)


Group website: https://www.chemie.unibas.ch/~anatole/