Teodoro Laino
IBM Research - Zurich(CH)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Advanced Text Analysis Techniques, Topic Modeling, Machine Learning in Bioinformatics
Most-Cited Works
- → CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations(2020)3,821 cited
- → “Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models(2018)465 cited
- → Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy(2020)449 cited
- → Surface-assisted cyclodehydrogenation provides a synthetic route towards easily processable and chemically tailored nanographenes(2010)448 cited
- → Accelerating materials discovery using artificial intelligence, high performance computing and robotics(2022)357 cited
- → Mapping the space of chemical reactions using attention-based neural networks(2021)303 cited
- → Extraction of organic chemistry grammar from unsupervised learning of chemical reactions(2021)283 cited
- → An Efficient Real Space Multigrid QM/MM Electrostatic Coupling(2005)280 cited
- → Solid-State Electrolytes: Revealing the Mechanisms of Li-Ion Conduction in Tetragonal and Cubic LLZO by First-Principles Calculations(2014)251 cited
- → Prediction of chemical reaction yields using deep learning(2021)249 cited