Overview of Computational Methods and Machine Learning: Panel Discussion

By Brett Matthew Savoie1; Pradeep Kumar Gurunathan2; Peilin Liao3; Xiulin Ruan4; Guang Lin4

1. Chemical Engineering, Purdue University, West Lafayette, IN 2. Chemistry, Purdue University, West Lafayette, IN 3. Materials Engineering, Purdue University, West Lafayette, IN 4. Mechanical Engineering, Purdue University, West Lafayette, IN

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Abstract

The individual Panel Talks which accompanies this discussion can be found here.

  • Why do we need experiments?
  • Are your methods “descriptive” or “predictive”?
  • Do you work with any other theory/simulation groups?
  • On the 5 year timescale: is machine-learning hype or a real game-changer?
  • On the 20 year timescale: is machine-learning hype or a real game-changer?

Sponsored by

Netork for Computational Nanotechnology

Cite this work

Researchers should cite this work as follows:

  • Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin (2019), "Overview of Computational Methods and Machine Learning: Panel Discussion," https://nanohub.org/resources/30761.

    BibTex | EndNote

Time

Location

Burton Morgan, Room 121, Purdue University, West Lafayette, IN

Tags

  1. algorithms
  2. chemistry
  3. computational chemistry
  4. machine learning
  5. QM/MM methods