| Chemcrow: Augmenting large-language models with chemistry tools AM Bran, S Cox, O Schilter, C Baldassari, AD White, P Schwaller arXiv preprint arXiv:2304.05376, 2023 | 135 | 2023 |
| Augmenting large language models with chemistry tools AM Bran, S Cox, O Schilter, C Baldassari, A White, P Schwaller NeurIPS 2023 AI for Science Workshop, 2023 | 14 | 2023 |
| Designing catalysts with deep generative models and computational data. A case study for Suzuki cross coupling reactions O Schilter, A Vaucher, P Schwaller, T Laino Digital discovery 2 (3), 728-735, 2023 | 11 | 2023 |
| Gt4sd: Generative toolkit for scientific discovery M Manica, J Cadow, D Christofidellis, A Dave, J Born, D Clarke, ... arXiv e-prints, arXiv: 2207.03928, 2022 | 9 | 2022 |
| The Role of AI in Driving the Sustainability of the Chemical Industry A Toniato, O Schilter, T Laino Chimia 77 (3), 144-149, 2023 | 6 | 2023 |
| Prediction of phase diagrams and associated phase structural properties F Zipoli, V Viterbo, O Schilter, L Kahle, T Laino Industrial & Engineering Chemistry Research 61 (24), 8378-8389, 2022 | 5 | 2022 |
| Accelerating material design with the generative toolkit for scientific discovery M Manica, J Born, J Cadow, D Christofidellis, A Dave, D Clarke, ... npj Computational Materials 9 (1), 69, 2023 | 3 | 2023 |
| CMD+ V for chemistry: Image to chemical structure conversion directly done in the clipboard OT Schilter, T Laino, P Schwaller Applied AI Letters, e91, 2024 | 1 | 2024 |
| Deep learning assisted Suzuki cross coupling catalyst design O Schilter, F Zipoli, A Vaucher, T Laino American Chemical Society (ACS) Fall Meeting, 2022 | 1 | 2022 |
| Advanced Data-Driven Manufacturing T Gaudin, O Schilter, F Zipoli, T Laino ERCIM News 122, 45, 2020 | 1 | 2020 |
| Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes O Schilter, DP Gutierrez, LM Folkmann, A Castrogiovanni, A García-Durán, ... Chemical Science, 2024 | | 2024 |
| Unveiling the Secrets of H-NMR Spectroscopy: A Novel Approach Utilizing Attention Mechanisms O Schilter, M Alberts, F Zipoli, AC Vaucher, P Schwaller, T Laino AI for Accelerated Materials Design-NeurIPS 2023 Workshop, 2023 | | 2023 |
| Using Foundation Models to Promote Digitization and Reproducibility in Scientific Experimentation A Thakkar, A Giovannini, A Foncubierta, C Baldassari, D Christofidellis, ... NeurIPS 2023 AI for Science Workshop, 2023 | | 2023 |
| Predicting the right Reaction Solvents in Organic Synthesis using Artificial Intelligence O Schilter, C Baldassari, T Laino, P Schwaller American Chemical Society (ACS) Fall Meeting, 2023 | | 2023 |
| Predicting solvents with the help of Artificial Intelligence OT Schilter, C Baldassari, T Laino, P Schwaller | | 2023 |
| Accelerating Material Design with the Generative Toolkit for Scientific Discovery (GT4SD) M Manica, J Cadow, D Christofidellis, A Dave, J Born, D Clarke, ... American Chemical Society (ACS) Fall Meeting, 2022 | | 2022 |
| Electronic Supporting Information: Designing catalysts with deep generative models and computational data. A case study for Suzuki cross coupling reactions O Schilter, A Vaucher, P Schwallerb, T Lainoa | | |
