Teodoro Laino
Teodoro Laino
IBM Research Zurich
E-mailová adresa ověřena na: - Domovská stránka
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
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
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
" 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
A revisited picture of the mechanism of glycerol dehydration
T Laino, C Tuma, A Curioni, E Jochnowitz, S Stolz
The Journal of Physical Chemistry A 115 (15), 3592-3595, 2011
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
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Články 1–20