Follow
Matteo Manica
Matteo Manica
IBM Research
Verified email at zurich.ibm.com - Homepage
Title
Cited by
Cited by
Year
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
13342021
Bloom: A 176b-parameter open-access multilingual language model
T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
12892023
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
4122018
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
1252019
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
972020
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
83*2021
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
762021
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
752020
Biocatalysed synthesis planning using data-driven learning
D Probst, M Manica, YG Nana Teukam, A Castrogiovanni, F Paratore, ...
Nature communications 13 (1), 964, 2022
692022
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
692020
Regression transformer enables concurrent sequence regression and generation for molecular language modelling
J Born, M Manica
Nature Machine Intelligence 5 (4), 432-444, 2023
62*2023
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
472023
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
432020
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
39*2021
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
342018
PIMKL: Pathway-induced multiple kernel learning
M Manica, J Cadow, R Mathis, MR Martínez
NPJ Systems Biology and Applications 5 (1), 1-8, 2019
322019
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
312018
Active site sequence representations of human kinases outperform full sequence representations for affinity prediction and inhibitor generation: 3D effects in a 1D model
J Born, T Huynh, A Stroobants, WD Cornell, M Manica
Journal of Chemical Information and Modeling 62 (2), 240-257, 2021
222021
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
212023
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks
M Filipavicius, M Manica, J Cadow, MR Martinez
NeurIPS 2020 Workshop on Machine Learning for Structural Biology, 2020
192020
The system can't perform the operation now. Try again later.
Articles 1–20