Tuning Correlation Effects with Electron–Phonon Interactions

Tuning Correlation Effects with Electron–Phonon Interactions

Model Tuning with Canonical Correlation

4 Knowledge of the relationship between model parameters and forecast quantities is 5 useful because it can aid in setting the values of the former for the purpose of having 6 a desired effect on the latter. Here, it is proposed that a well-established multivariate 7 statistical method known as Canonical Correlation Analysis can be formulated to gauge 8 the strength of that relationship. The me...

Model Tuning with Canonical Correlation Analysis

Knowledge of the relationship between model parameters and forecast quantities is useful because it can aid in setting the values of the former for the purpose of having a desired effect on the latter. Here it is proposed that a well-establishedmultivariate statistical method known as canonical correlation analysis can be formulated to gauge the strength of that relationship. Themethod is appli...

Tuning aryl, hydrazine radical cation electronic interactions using substituent effects.

Absorption spectra for 2,3-diaryl-2,3-diazabicyclo[2.2.2]octane radical cations (2(X)(*+)) and for their monoaryl analogues 2-tert-butyl-3-aryl-2,3-diazabicyclo[2.2.2]octane radical cations (1(X)(*+)) having para chloro, bromo, iodo, cyano, phenyl, and nitro substituents are reported and compared with those for the previously reported 1- and 2(H)(*+) and 1- and 2(OMe)(*+). The calculated geomet...

Evaluation Function Tuning via Ordinal Correlation

Heuristic search effectiveness depends directly upon the quality of heuristic evaluations of states in the search space. We show why ordinal correlation is relevant to heuristic search, present a metric for assessing the quality of a static evaluation function, and apply it to learn feature weights for a computer chess