Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800115
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- Publication type:
- Article
Works matching IS 18681743 AND DT 2019 AND VI 38 AND IP 4
Results: 7
1
2
Bimolecular Nucleophilic Substitution Reactions: Predictive Models for Rate Constants and Molecular Reaction Pairs Analysis.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800104
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- Publication type:
- Article
3
A Survey of Multi‐task Learning Methods in Chemoinformatics.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800108
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- Publication type:
- Article
4
Cover Picture: (Mol. Inf. 4/2019).
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201980401
- Publication type:
- Article
5
Alkanes with the First Three Maximal/Minimal Modified First Zagreb Connection Indices.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800116
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- Publication type:
- Article
6
Random Forest Model with Combined Features: A Practical Approach to Predict Liquid‐crystalline Property.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800095
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- Publication type:
- Article
7
A Neural Network QSPR Model for Accurate Prediction of Flash Point of Pure Hydrocarbons.
- Published in:
- Molecular Informatics, 2019, v. 38, n. 4, p. N.PAG, doi. 10.1002/minf.201800094
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- Publication type:
- Article