| CP2K: An electronic structure and molecular dynamics software package-Quickstep: Efficient and accurate electronic structure calculations TD Kühne, M Iannuzzi, M Del Ben, VV Rybkin, P Seewald, F Stein, ... The Journal of Chemical Physics 152 (19), 2020 | 2790 | 2020 |
| Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction P Schwaller, T Laino, T Gaudin, P Bolgar, CA Hunter, C Bekas, AA Lee ACS central science 5 (9), 1572-1583, 2019 | 988 | 2019 |
| Surface-assisted cyclodehydrogenation provides a synthetic route towards easily processable and chemically tailored nanographenes M Treier, CA Pignedoli, T Laino, R Rieger, K Müllen, D Passerone, ... Nature chemistry 3 (1), 61-67, 2011 | 486 | 2011 |
| " Found in Translation": Predicting Outcome of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models P Schwaller, T Gaudin, D Lanyi, C Bekas, T Laino Chemical Science 9, 6091-6098, 2017 | 462 | 2017 |
| Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy P Schwaller, R Petraglia, V Zullo, VH Nair, RA Haeuselmann, R Pisoni, ... Chemical science 11 (12), 3316-3325, 2020 | 379 | 2020 |
| Prediction of chemical reaction yields using deep learning P Schwaller, AC Vaucher, T Laino, JL Reymond Machine learning: science and technology 2 (1), 015016, 2021 | 319* | 2021 |
| An efficient real space multigrid QM/MM electrostatic coupling T Laino, F Mohamed, A Laio, M Parrinello Journal of Chemical Theory and Computation 1 (6), 1176-1184, 2005 | 310 | 2005 |
| Mapping the space of chemical reactions using attention-based neural networks P Schwaller, D Probst, AC Vaucher, VH Nair, D Kreutter, T Laino, ... Nature machine intelligence 3 (2), 144-152, 2021 | 291 | 2021 |
| Solid-state electrolytes: revealing the mechanisms of Li-ion conduction in tetragonal and cubic LLZO by first-principles calculations K Meier, T Laino, A Curioni The Journal of Physical Chemistry C 118 (13), 6668-6679, 2014 | 258 | 2014 |
| Accelerating materials discovery using artificial intelligence, high performance computing and robotics EO Pyzer-Knapp, JW Pitera, PWJ Staar, S Takeda, T Laino, DP Sanders, ... npj Computational Materials 8 (1), 84, 2022 | 233 | 2022 |
| Extraction of organic chemistry grammar from unsupervised learning of chemical reactions P Schwaller, B Hoover, JL Reymond, H Strobelt, T Laino Science Advances 7 (15), eabe4166, 2021 | 228 | 2021 |
| Automated extraction of chemical synthesis actions from experimental procedures AC Vaucher, F Zipoli, J Geluykens, VH Nair, P Schwaller, T Laino Nature Communications 11, 3601, 2020 | 201 | 2020 |
| An efficient linear-scaling electrostatic coupling for treating periodic boundary conditions in QM/MM simulations T Laino, F Mohamed, A Laio, M Parrinello Journal of chemical theory and computation 2 (5), 1370-1378, 2006 | 200 | 2006 |
| Transfer learning enables the molecular transformer to predict regio-and stereoselective reactions on carbohydrates G Pesciullesi, P Schwaller, T Laino, JL Reymond Nature communications 11 (1), 4874, 2020 | 182 | 2020 |
| Exploring chemical space using natural language processing methodologies for drug discovery H Öztürk, A Özgür, P Schwaller, T Laino, E Ozkirimli Drug Discovery Today 25 (4), 689-705, 2020 | 166 | 2020 |
| Mechanisms of propylene glycol and triacetin pyrolysis T Laino, C Tuma, P Moor, E Martin, S Stolz, A Curioni The journal of physical chemistry A 116 (18), 4602-4609, 2012 | 141 | 2012 |
| Machine intelligence for chemical reaction space P Schwaller, AC Vaucher, R Laplaza, C Bunne, A Krause, C Corminboeuf, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (5), e1604, 2022 | 113 | 2022 |
| Relationship between structure and optical properties in green fluorescent proteins: a quantum mechanical study of the chromophore environment T Laino, R Nifosı̀, V Tozzini Chemical physics 298 (1-3), 17-28, 2004 | 112 | 2004 |
| CogMol: Target-specific and selective drug design for COVID-19 using deep generative models V Chenthamarakshan, P Das, S Hoffman, H Strobelt, I Padhi, KW Lim, ... Advances in Neural Information Processing Systems 33, 4320-4332, 2020 | 109 | 2020 |
| Unifying molecular and textual representations via multi-task language modelling D Christofidellis, G Giannone, J Born, O Winther, T Laino, M Manica International Conference on Machine Learning, 6140-6157, 2023 | 96 | 2023 |
Philippe SchwallerAssistant Professor, Laboratory of Artificial Chemical Intelligence - EPFLVerified email at epfl.ch
