<description>&lt;p&gt;Our guest for this episode is Prof. Dr. O. Anatole von Lilienfeld from the University of Basel.&lt;br/&gt;&lt;br/&gt;Some relevant papers:&lt;br/&gt;&lt;br/&gt;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Huang, B., and von Lilienfeld, O. A., &lt;b&gt;The ‘DNA’ of Chemistry: Scalable Quantum Machine Learning with ‘Amons.’&lt;/b&gt; a&lt;em&gt;rXiv:1707.04146,&lt;/em&gt; (2017)&lt;/li&gt;&lt;li&gt;Ramakrishnan, R., Dral, P. O., Rupp, M., and von Lilienfeld, O. A., &lt;b&gt;Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.&lt;/b&gt; &lt;em&gt;Journal of Chemical Theory and Computation, &lt;/em&gt;doi:10.1021/acs.jctc.5b00099 (2015)&lt;/li&gt;&lt;li&gt;Rupp, M., Tkatchenko, A., Müller, K.-R., and von Lilienfeld, O. A., &lt;b&gt;Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning.&lt;/b&gt; &lt;em&gt;Physical Review Letters, &lt;/em&gt;doi:10.1103/PhysRevLett.108.058301 (2012)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;br/&gt;Group website: &lt;a href='https://www.chemie.unibas.ch/~anatole/'&gt;https://www.chemie.unibas.ch/~anatole/&lt;/a&gt;&lt;/p&gt;</description>

Materials and Megabytes

Stanford Materials Computation and Theory Group, Qian Yang's lab at the University of Connecticut

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

JAN 25, 201922 MIN
Materials and Megabytes

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

JAN 25, 201922 MIN

Description

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/