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Category:Machine Learning
This section describes the methodology used for force-field generation using machine learning.
- Besides the usual input files (INCAR, POSCAR, etc.) the machine learning force field method requires the following input files:
ABCAR Ab initio data used to create the training data.
FFCAR File containing force field parameters.
- The machine learning force field method generates the following output files:
ML_LOGFILE Main output file for the machine learning force field method.
ABNCAR New abinitio data (used as ABCAR in the next run).
REGCAR Output file summarizing regression results.
HISCAR Output file summarizing the histogram data.
FFNCAR File containing new force field parameters (used as FFCAR in the next run).
ML_EATOM Output file containing local atomic energies
ML_HEAT Output file including local heat flux
All INCAR tags belonging to the machine learning force field method start with the prefix ML_FF_. Input tags that are related to the many-body term end with _MB.
Theoretical Background
Pages in category "Machine Learning"
The following 55 pages are in this category, out of 55 total.
M
- Machine learning force field calculations: Basics
- Machine learning force field: Theory
- ML AB
- ML ABN
- ML AFILT2
- ML CDOUB
- ML CSIG
- ML CSLOPE
- ML CTIFOR
- ML EATOM
- ML EATOM REF
- ML EPS LOW
- ML FF
- ML FFN
- ML HEAT
- ML HIS
- ML IAFILT2
- ML ICOUPLE
- ML ICRITERIA
- ML IREG
- ML ISCALE TOTEN
- ML ISTART
- ML IWEIGHT
- ML LAFILT2
- ML LCOUPLE
- ML LEATOM
- ML LHEAT
- ML LMAX2
- ML LMLFF
- ML LOGFILE
- ML LSPARSDES
- ML MB
- ML MCONF
- ML MCONF NEW
- ML MHIS
- ML MRB1
- ML MRB2
- ML NATOM COUPLED
- ML NHYP
- ML NMDINT
- ML NRANK SPARSDES
- ML RCOUPLE
- ML RCUT1
- ML RCUT2
- ML RDES SPARSDES
- ML REG
- ML SIGV0
- ML SIGW0
- ML SION1
- ML SION2
- ML W1
- ML WTIFOR
- ML WTOTEN
- ML WTSIF
- ML XMIX
