| Comment on “A new parametrizable model of molecular electronic structure”[J. Chem. Phys. 135, 134120 (2011)] KR Briling The Journal of chemical physics 147 (15), 157101, 2017 | 16 | 2017 |
| SPA HM: the spectrum of approximated Hamiltonian matrices representations A Fabrizio, KR Briling, C Corminboeuf Digital Discovery 1 (3), 286-294, 2022 | 13 | 2022 |
| Learning on-top: Regressing the on-top pair density for real-space visualization of electron correlation A Fabrizio, KR Briling, DD Girardier, C Corminboeuf The Journal of Chemical Physics 153 (20), 204111, 2020 | 12 | 2020 |
| Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity A Fabrizio, K Briling, A Grisafi, C Corminboeuf CHIMIA International Journal for Chemistry 74 (4), 232-236, 2020 | 12 | 2020 |
| Atomic effective potentials for starting molecular electronic structure calculations DN Laikov, KR Briling Theoretical Chemistry Accounts 139, 1-4, 2020 | 8 | 2020 |
| 3DReact: Geometric Deep Learning for Chemical Reactions P van Gerwen, KR Briling, C Bunne, VR Somnath, R Laplaza, A Krause, ... Journal of Chemical Information and Modeling, 2024 | 7* | 2024 |
| Impact of quantum-chemical metrics on the machine learning prediction of electron density KR Briling, A Fabrizio, C Corminboeuf The Journal of Chemical Physics 155 (2), 024107, 2021 | 6 | 2021 |
| Learning the Exciton Properties of Azo-dyes S Vela, A Fabrizio, KR Briling, C Corminboeuf The Journal of Physical Chemistry Letters 12, 5957-5962, 2021 | 5 | 2021 |
| SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations KR Briling, Y Calvino Alonso, A Fabrizio, C Corminboeuf Journal of Chemical Theory and Computation 20 (3), 1108-1117, 2024 | 4 | 2024 |
| Benchmarking machine-readable vectors of chemical reactions on computed activation barriers P van Gerwen, KR Briling, YC Alonso, M Franke, C Corminboeuf Digital Discovery 3 (5), 932-943, 2024 | 4 | 2024 |
| Heptalene Synthesis by Addition of Aryl Acetylenes to Azulenes KR Briling, DN Laikov Russian Journal of Organic Chemistry 56, 569-575, 2020 | 4 | 2020 |
| Integer linear programming for unsupervised training set selection in molecular machine learning M Haeberle, P van Gerwen, R Laplaza, KR Briling, J Weinreich, ... arXiv preprint arXiv:2410.16122, 2024 | | 2024 |
| Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties K Briling EPFL, 2024 | | 2024 |
| Получение гепталенов присоединением арилацетиленов к азуленам КР Брилинг, ДН Лайков Журнал органической химии 56 (4), 514-521, 2020 | | 2020 |
Alberto FabrizioEPFLBestätigte E-Mail-Adresse bei epfl.ch
