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MCLF

Machine learned correcting functionals (MCLFs) is a method that uses machine learning to extrapolate between two density functional approximations and allow for faster and more accurate ab-initio calculations in molecular sciences.

IACS RESEARCHERS
Sebastian Dick, Physics and Astronomy

See pagesposters
See pagespresentations
See pagesproducts
- See pagesOpen Source Textbook
  - Computational Hydrodynamics for Astrophysics
- See pagesSoftware
  - Astronomy Animations
  - Castro
  - Epskw
  - FTAPI
  - HIFIR
  - Hydro1d
  - Hydro_examples
  - Kist
  - MADNESS
  - Maestro
  - MAPPPD
  - MCLF
  - MediaRank
  - MolStat
  - NamePrism
  - NWChem-Ex
  - OpenMP to Tapir
  - PIMD-F90
  - Pyro
  - RedTyp
  - Spectrumfitter
  - The Flash Code
  - Transport For Inertial Confinement Fusion
  - vLGP
- See pagesVirtual Supercomputer
  - virtu-ALL-izer
See pagesprojects
See pagespublications
Research Day

See pagesposters
See pagespresentations
See pagesproducts
- See pagesOpen Source Textbook
  - Computational Hydrodynamics for Astrophysics
- See pagesSoftware
  - Astronomy Animations
  - Castro
  - Epskw
  - FTAPI
  - HIFIR
  - Hydro1d
  - Hydro_examples
  - Kist
  - MADNESS
  - Maestro
  - MAPPPD
  - MCLF
  - MediaRank
  - MolStat
  - NamePrism
  - NWChem-Ex
  - OpenMP to Tapir
  - PIMD-F90
  - Pyro
  - RedTyp
  - Spectrumfitter
  - The Flash Code
  - Transport For Inertial Confinement Fusion
  - vLGP
- See pagesVirtual Supercomputer
  - virtu-ALL-izer
See pagesprojects
See pagespublications
Research Day