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A few years ago, I wrote a paper with other collaborators[1] on how to use dimensional analysis as a way to improve feature selection, that can in turn improve

A few years ago, I wrote a paper with other collaborators[1] on how to use dimensional analysis as a way to improve feature selection, that can in turn improve machine learning performance for physical/chemical systems, especially those with small datasets. Full manuscript is available through researchgate[2] [1] https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.8b02837 https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.8b02837 [2] https://www.researchgate.net/profile/Janakiraman-Balachandran/publication/329540911_Machine_Learning_Constrained_with_Dimensional_Analysis_and_Scaling_Laws_Simple_Transferable_and_Interpretable_Models_of_Materials_from_Small_Datasets/links/5e55d4e7299bf1bdb83b192d/Machine-Learning-Constrained-with-Dimensional-Analysis-and-Scaling-Laws-Simple-Transferable-and-Interpretable-Models-of-Materials-from-Small-Datasets.pdf https://www.researchgate.net/profile/Janakiraman-Balachandra...

sroussey 4y ago
This is interesting! Where can I find more information about people using ML models for the physical world that is not drug discovery or anything about proteins?
- adgjlsfhk1 4y ago
  if you look into sciml stuff in the Julia community there's a bunch. some example use cases are trajectory optimization, and accelerating climate simulation. often these ML models are referred to as "surrogate models". let me know if you have more questions, I can probably point you in the right direction.
  - sroussey 4y ago
    I’m thinking materials… predicting the effect of doping for semiconductors, etc. Or, on a different angle, shape of rotors and how they affect sound of their movements.
    - ChrisRackauckas 4y ago
      > predicting the effect of doping for semiconductors, etc. Here you go, a whole Julia SciML thesis on this topic: https://dspace.mit.edu/handle/1721.1/144946 https://dspace.mit.edu/handle/1721.1/144946
- wanderingmind 4y ago
  ArXiV has lot of subsections like materials, condensed matter where you can find lot of interesting applications

sroussey 4y ago

This is interesting! Where can I find more information about people using ML models for the physical world that is not drug discovery or anything about proteins?

adgjlsfhk1 4y ago
if you look into sciml stuff in the Julia community there's a bunch. some example use cases are trajectory optimization, and accelerating climate simulation. often these ML models are referred to as "surrogate models". let me know if you have more questions, I can probably point you in the right direction.
- sroussey 4y ago
  I’m thinking materials… predicting the effect of doping for semiconductors, etc. Or, on a different angle, shape of rotors and how they affect sound of their movements.
  - ChrisRackauckas 4y ago
    > predicting the effect of doping for semiconductors, etc. Here you go, a whole Julia SciML thesis on this topic: https://dspace.mit.edu/handle/1721.1/144946 https://dspace.mit.edu/handle/1721.1/144946
wanderingmind 4y ago
ArXiV has lot of subsections like materials, condensed matter where you can find lot of interesting applications