| Multitask prompted training enables zero-shot task generalization V Sanh, A Webson, C Raffel, SH Bach, L Sutawika, Z Alyafeai, A Chaffin, ... The Tenth International Conference on Learning Representations (ICLR 2022), 2021 | 1854 | 2021 |
| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1805 | 2023 |
| Mixed-precision in-memory computing M Le Gallo, A Sebastian, R Mathis, M Manica, H Giefers, T Tuma, C Bekas, ... Nature Electronics 1 (4), 246-253, 2018 | 464 | 2018 |
| Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders M Manica, A Oskooei, J Born, V Subramanian, J Sáez-Rodríguez, ... Molecular Pharmaceutics, 2019 | 141 | 2019 |
| CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models V Chenthamarakshan, P Das, I Padhi, H Strobelt, KW Lim, B Hoover, ... Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020 | 128* | 2020 |
| Regression transformer enables concurrent sequence regression and generation for molecular language modelling J Born, M Manica Nature Machine Intelligence 5 (4), 432-444, 2023 | 121 | 2023 |
| Biocatalysed synthesis planning using data-driven learning D Probst, M Manica, YG Nana Teukam, A Castrogiovanni, F Paratore, ... Nature communications 13 (1), 964, 2022 | 97 | 2022 |
| PaccMannRL: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning J Born, M Manica, A Oskooei, J Cadow, G Markert, MR Martínez iScience 2021 / RECOMB 2020, 2021 | 96* | 2021 |
| Unifying molecular and textual representations via multi-task language modelling D Christofidellis, G Giannone, J Born, O Winther, T Laino, M Manica Proceedings of the 40th International Conference on Machine Learning (ICML 2023), 2023 | 94 | 2023 |
| Guiding attention in sequence-to-sequence models for dialogue act prediction P Colombo, E Chapuis, M Manica, E Vignon, G Varni, C Clavel Proceedings of the AAAI conference on artificial intelligence 34 (05), 7594-7601, 2020 | 90 | 2020 |
| On the role of artificial intelligence in medical imaging of COVID-19 J Born, D Beymer, D Rajan, A Coy, VV Mukherjee, M Manica, P Prasanna, ... Patterns 2 (6), 2021 | 85 | 2021 |
| Hierarchical pre-training for sequence labelling in spoken dialog E Chapuis, P Colombo, M Manica, M Labeau, C Clavel Findings of the Association for Computational Linguistics: EMNLP 2020, 2020 | 79 | 2020 |
| PaccMann: a web service for interpretable anticancer compound sensitivity prediction J Cadow, J Born, M Manica, A Oskooei, M Rodríguez Martínez Nucleic acids research 48 (W1), W502-W508, 2020 | 54 | 2020 |
| Data-driven Molecular Design for Discovery and Synthesis of Novel Ligands-A case study on SARS-CoV-2 J Born, M Manica, J Cadow, G Markert, M Filipavicius, NA Mill, ... Machine Learning: Science and Technology / ICML 2020 Workshop on …, 2021 | 46 | 2021 |
| Network-based biased tree ensembles (NetBiTE) for drug sensitivity prediction and drug sensitivity biomarker identification in cancer A Oskooei, M Manica, R Mathis, MR Martínez Scientific Reports 9, 2018 | 42 | 2018 |
| PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks A Oskooei, J Born, M Manica, V Subramanian, J Sáez-Rodríguez, ... NeurIPS 2018 Workshop on Machine Learning for Molecule and Materials, 2018 | 40 | 2018 |
| PIMKL: Pathway-induced multiple kernel learning M Manica, J Cadow, R Mathis, MR Martínez NPJ Systems Biology and Applications 5 (1), 1-8, 2019 | 35 | 2019 |
| Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language NH Park, M Manica, J Born, JL Hedrick, T Erdmann, DY Zubarev, ... Nature Communications 14 (1), 3686, 2023 | 31 | 2023 |
| 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 | 31* | 2023 |
| Chemical representation learning for toxicity prediction J Born, G Markert, N Janakarajan, TB Kimber, A Volkamer, MR Martínez, ... Digital Discovery 2 (3), 674-691, 2023 | 31 | 2023 |
María Rodríguez Martínez (ORCID: 00...IBM Research - ZürichVerified email at zurich.ibm.com
