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Descriptors

I Grillo, G Urquiza-Carvalho, G Rocha, Quantum chemical descriptors based on semiempirical methods for large biomolecules, JCP 158, 201001 (2023) – doi

R Todeschini, V Consonni, Molecular Descriptors for Chemoinformatics (Wiley, 2009)

C Hansch, A Leo, R W Taft, A Survey of Hammett Substituent Constants and Resonance and Field Parameters, CR 97, 165 (1991)


L M Ghiringhelli, J Vybiral, E Ahmetcik, R Ouyang, S V Levchenko, C Draxl, M Scheffler, Learning physical descriptors for materials science by compressed sensing, New J Phys 19, 023017 (2017)

L M Ghiringhelli, J Vybiral, S V Levchenko, C Draxl, M Scheffler, Big Data of Materials Science: Critical Role of the Descriptor, PRL 114, 105503 (2015)

T Papp, L Kollar, T Kegl, Employment of quantum chemical descriptors for Hammett constants: Revision Suggested for the acetoxy substituent, CPL 588, 51 (2013)

T M Krygowski, N Sadlej-Sosnowska, Towards physical interpretation of Hammett constants: charge transferred between active regions of substituents and a functional group, Struct Chem 22, 17 (2011)

Y Takahata, A Dos Santos Marques, Accurate core-electron binding energy shifts from density functional theory, J Electron Spectrosc Relat Phenom 80, 178 (2010)

P Ertl, Simple Quantum Chemical Parameters as an Alternative to the Hammett Sigma Constants in QSAR Studies, Quant Struct Act Relat 16, 377 (1997)

Structure encoding

C Bilodeau, W Jin, T Jaakkola, R Barzilay, K Jensen, Generative models for molecular discovery: Recent advances and challenges, WCMS 12, e1608 (2022)

D Wigh, J Goodman, A Lapkin, A review of molecular representation in the age of machine learning, WCMS 12, e1603 (2022)

F Musil, A Grisafi, A Bartok, C Ortner, G Csanyi, M Ceriotti, Physics-Inspired Structural Representations for Molecules and Materials, CR 121, 9759 (2021)


A Grisafi, M Ceriotti, Incorporating long-range physics in atomic-scale machine learning, JCP 151, 204105 (2019)

A Grisafi, A Fabrizio, B Meyer, D Wilkins, C Corminboeuf, M Ceriotti, Transferable Machine-Learning Model of the Electron Density, ACS Cent Sci 5, 57 (2019)

R Gomez-Bombarelli, J N Wei, D Duvenaud, J M Hernandez-Lobato, B Sanchez-Lengeling, D Sheberla, J Aguilera-Iparraguirre, T D Hirzel, R P Adams, A Aspuru-Guzik, Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules, ACS Cent Sci 4, 268 (2018)