Matteo Manica
Matteo Manica
IBM Research
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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
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
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
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
Bloom: A 176b-parameter open-access multilingual language model
TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
arXiv preprint arXiv:2211.05100, 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
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), 100269, 2021
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
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
Biocatalysed synthesis planning using data-driven learning
D Probst, M Manica, YG Nana Teukam, A Castrogiovanni, F Paratore, ...
Nature communications 13 (1), 964, 2022
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
PIMKL: Pathway-induced multiple kernel learning
M Manica, J Cadow, R Mathis, MR Martínez
NPJ Systems Biology and Applications 5 (1), 1-8, 2019
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
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
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
Convergent network effects along the axis of gene expression during prostate cancer progression
K Charmpi, T Guo, Q Zhong, U Wagner, R Sun, NC Toussaint, CE Fritz, ...
Genome Biology 21 (1), 1-31, 2020
An information extraction and knowledge graph platform for accelerating biochemical discoveries
M Manica, C Auer, V Weber, F Zipoli, M Dolfi, P Staar, T Laino, C Bekas, ...
KDD 2019 Workshop on Applied Data Science for Healthcare, 2019
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
Context-specific interaction networks from vector representation of words
M Manica, R Mathis, J Cadow, M Rodríguez Martínez
Nature Machine Intelligence 1 (4), 181-190, 2019
Interaction network inference from vector representation of words
M Manica, R Mathis, MR Martinez, K Bekas
US Patent 10,593,422, 2020
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