Matteo Manica

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 40

Top Topics

Mass Spectrometry

Vector Representation

Reinforcement Learning

Top Venues

J. Chem. Inf. Model.

EMNLP (Findings)

Publications

Jannis Born, Matteo Manica
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling. Nat. Mac. Intell. 5 (4) (2023)
Girmaw Abebe Tadesse, Jannis Born, Celia Cintas, William Ogallo, Dmitry Zubarev, Matteo Manica, Komminist Weldemariam
Domain-agnostic and Multi-level Evaluation of Generative Models. CoRR (2023)
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
Unifying Molecular and Textual Representations via Multi-task Language Modelling. CoRR (2023)
Daniele Comi, Dimitrios Christofidellis, Pier Francesco Piazza, Matteo Manica
Zero-Shot-BERT-Adapters: a Zero-Shot Pipeline for Unknown Intent Detection. EMNLP (Findings) (2023)
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
Unifying Molecular and Textual Representations via Multi-task Language Modelling. ICML (2023)
Varun S. Sharma, Andrea Fossati, Rodolfo Ciuffa, Marija Buljan, Evan G. Williams, Zhen Chen, Wenguang Shao, Patrick G. A. Pedrioli, Anthony W. Purcell, María Rodríguez Martínez, Jiangning Song, Matteo Manica, Ruedi Aebersold, Chen Li
PCfun: a hybrid computational framework for systematic characterization of protein complex function. Briefings Bioinform. 23 (4) (2022)
Victor Sanh, Albert Webson, Colin Raffel, Stephen Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush
Multitask Prompted Training Enables Zero-Shot Task Generalization. ICLR (2022)
Matteo Manica, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Jannis Born, Dean Clarke, Yves Gaetan Nana Teukam, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang-Han Hsu, Federico Zipoli, Oliver Schilter, Giorgio Giannone, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith
GT4SD: Generative Toolkit for Scientific Discovery. CoRR (2022)
Jannis Born, Yoel Shoshan, Tien Huynh, Wendy D. Cornell, Eric J. Martin, Matteo Manica
On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction. J. Chem. Inf. Model. 62 (18) (2022)
Jannis Born, Tien Huynh, Astrid Stroobants, Wendy D. Cornell, Matteo Manica
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model. J. Chem. Inf. Model. 62 (2) (2022)
Jannis Born, Matteo Manica
Regression Transformer: Concurrent Conditional Generation and Regression by Blending Numerical and Textual Tokens. CoRR (2022)
Nikita Janakarajan, Jannis Born, Matteo Manica
A Fully Differentiable Set Autoencoder. KDD (2022)
Daniele Comi, Dimitrios Christofidellis, Pier Francesco Piazza, Matteo Manica
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detection. CoRR (2022)
Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos, Hans Vandierendonck
Understood in Translation: Transformers for Domain Understanding. SDU@AAAI (2021)
Joris Cadow, Matteo Manica, Roland Mathis, Tiannan Guo, Ruedi Aebersold, María Rodríguez Martínez
On the feasibility of deep learning applications using raw mass spectrometry data. Bioinform. 37 (Supplement) (2021)
Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V. Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L. Shah, Emmanouil Karteris, Jan L. Robertus, Maria Gabrani, Michal Rosen-Zvi
On the role of artificial intelligence in medical imaging of COVID-19. Patterns 2 (6) (2021)
Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, Nikita Janakarajan, Antonio Cardinale, Teodoro Laino, María Rodríguez Martínez
Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2. Mach. Learn. Sci. Technol. 2 (2) (2021)
Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M. Rush
Multitask Prompted Training Enables Zero-Shot Task Generalization. CoRR (2021)
Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V. Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L. Shah, Emmanouil Karteris, Jan L. Robertus, Maria Gabrani, Michal Rosen-Zvi
On the role of artificial intelligence in medical imaging of COVID-19. Patterns 2 (8) (2021)
Emile Chapuis, Pierre Colombo, Matteo Manica, Matthieu Labeau, Chloé Clavel
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog. EMNLP (Findings) (2020)
Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, Chloé Clavel
Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction. AAAI (2020)
Matteo Manica, Raphael Polig, Mitra Purandare, Roland Mathis, Christoph Hagleitner, María Rodríguez Martínez
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 17 (6) (2020)
Joris Cadow, Jannis Born, Matteo Manica, Ali Oskooei, María Rodríguez Martínez
PaccMann: a web service for interpretable anticancer compound sensitivity prediction. Nucleic Acids Res. 48 (Webserver-Issue) (2020)
Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, María Rodríguez Martínez
on SARS-CoV-2: Designing antiviral candidates with conditional generative models. CoRR (2020)
Emile Chapuis, Pierre Colombo, Matteo Manica, Matthieu Labeau, Chloé Clavel
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog. CoRR (2020)
Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos, Hans Vandierendonck
Understood in Translation, Transformers for Domain Understanding. CoRR (2020)
Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. NeurIPS (2020)
Modestas Filipavicius, Matteo Manica, Joris Cadow, María Rodríguez Martínez
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks. CoRR (2020)
Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, Chloé Clavel
Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue. CoRR (2020)
Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, María Rodríguez Martínez
: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. RECOMB (2020)
Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, Chloé Clavel
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction. CoRR (2020)
Matteo Manica, Christoph Auer, Valéry Weber, Federico Zipoli, Michele Dolfi, Peter W. J. Staar, Teodoro Laino, Costas Bekas, Akihiro Fujita, Hiroki Toda, Shuichi Hirose, Yasumitsu Orii
An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries. CoRR (2019)
Matteo Manica, Ali Oskooei, Jannis Born, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders. CoRR (2019)
Matteo Manica, Roland Mathis, Joris Cadow, María Rodríguez Martínez
Context-specific interaction networks from vector representation of words. Nat. Mach. Intell. 1 (4) (2019)
Matteo Manica, Ali Oskooei, Jannis Born
AI Enables Explainable Drug Sensitivity Screenings. ERCIM News 2019 (118) (2019)
Atin Sood, Benjamin Elder, Benjamin Herta, Chao Xue, Costas Bekas, A. Cristiano I. Malossi, Debashish Saha, Florian Scheidegger, Ganesh Venkataraman, Gegi Thomas, Giovanni Mariani, Hendrik Strobelt, Horst Samulowitz, Martin Wistuba, Matteo Manica, Mihir R. Choudhury, Rong Yan, Roxana Istrate, Ruchir Puri, Tejaswini Pedapati
NeuNetS: An Automated Synthesis Engine for Neural Network Design. CoRR (2019)
Jannis Born, Matteo Manica, Ali Oskooei, María Rodríguez Martínez
Reinforcement learning-driven de-novo design of anticancer compounds conditioned on biomolecular profiles. CoRR (2019)
Ali Oskooei, Jannis Born, Matteo Manica, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez
PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks. CoRR (2018)
Ali Oskooei, Matteo Manica, Roland Mathis, María Rodríguez Martínez
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer. CoRR (2018)
Manuel Le Gallo, Abu Sebastian, Roland Mathis, Matteo Manica, Tomas Tuma, Costas Bekas, Alessandro Curioni, Evangelos Eleftheriou
Mixed-Precision Memcomputing. CoRR (2017)