Mixed-Precision Memcomputing. - Manuel Le Gallo; Abu Sebastian; Roland Mathis; Matteo Manica; Tomas Tuma; Costas Bekas; Alessandro Curioni; Evangelos Eleftheriou (CoRR, 2017)

Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer. - Ali Oskooei; Matteo Manica; Roland Mathis; María Rodríguez Martínez (CoRR, 2018)

PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks. - Ali Oskooei; Jannis Born; Matteo Manica; Vigneshwari Subramanian; Julio Sáez-Rodríguez; María Rodríguez Martínez (CoRR, 2018)

Exploring Multi-Modal Learning Approaches Towards Precision Medicine. - Matteo Manica (2018)

NeuNetS: An Automated Synthesis Engine for Neural Network Design. - 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; et al. (CoRR, 2019)

Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders. - Matteo Manica; Ali Oskooei; Jannis Born; Vigneshwari Subramanian; Julio Sáez-Rodríguez; María Rodríguez Martínez (CoRR, 2019)

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries. - 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 (CoRR, 2019)

Reinforcement learning-driven de-novo design of anticancer compounds conditioned on biomolecular profiles. - Jannis Born; Matteo Manica; Ali Oskooei; María Rodríguez Martínez (CoRR, 2019)

AI Enables Explainable Drug Sensitivity Screenings. - Matteo Manica; Ali Oskooei; Jannis Born (ERCIM News, 2019)

Context-specific interaction networks from vector representation of words. - Matteo Manica; Roland Mathis; Joris Cadow; María Rodríguez Martínez (Nat. Mach. Intell., 2019)

Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction. - Pierre Colombo; Emile Chapuis; Matteo Manica; Emmanuel Vignon; Giovanna Varni; Chloé Clavel (AAAI, 2020)

Hierarchical Pre-training for Sequence Labelling in Spoken Dialog. - Emile Chapuis; Pierre Colombo; Matteo Manica; Matthieu Labeau; Chloé Clavel (EMNLP (Findings), 2020)

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. - Vijil Chenthamarakshan; Payel Das; Samuel C. Hoffman; Hendrik Strobelt; Inkit Padhi; Kar Wai Lim; Benjamin Hoover; Matteo Manica; Jannis Born; Teodoro Laino; Aleksandra Mojsilovic (NeurIPS, 2020)

PaccMannRL: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. - Jannis Born; Matteo Manica; Ali Oskooei; Joris Cadow; María Rodríguez Martínez (RECOMB, 2020)

Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue. - Pierre Colombo; Emile Chapuis; Matteo Manica; Emmanuel Vignon; Giovanna Varni; Chloé Clavel (CoRR, 2020)

PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models. - Jannis Born; Matteo Manica; Joris Cadow; Greta Markert; Nil Adell Mill; Modestas Filipavicius; María Rodríguez Martínez (CoRR, 2020)

Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks. - Modestas Filipavicius; Matteo Manica; Joris Cadow; María Rodríguez Martínez (CoRR, 2020)

PaccMann: a web service for interpretable anticancer compound sensitivity prediction. - Joris Cadow; Jannis Born; Matteo Manica; Ali Oskooei; María Rodríguez Martínez (Nucleic Acids Res., 2020)

FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. - Matteo Manica; Raphael Polig; Mitra Purandare; Roland Mathis; Christoph Hagleitner; María Rodríguez Martínez (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Understood in Translation: Transformers for Domain Understanding. - Dimitrios Christofidellis; Matteo Manica; Leonidas Georgopoulos; Hans Vandierendonck (SDU@AAAI, 2021)

On the feasibility of deep learning applications using raw mass spectrometry data. - Joris Cadow; Matteo Manica; Roland Mathis; Tiannan Guo; Ruedi Aebersold; María Rodríguez Martínez (Bioinform., 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - 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; et al. (CoRR, 2021)

Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2. - Jannis Born; Matteo Manica; Joris Cadow; Greta Markert; Nil Adell Mill; Modestas Filipavicius; Nikita Janakarajan; Antonio Cardinale; Teodoro Laino; María Rodríguez Martínez (Mach. Learn. Sci. Technol., 2021)

On the role of artificial intelligence in medical imaging of COVID-19. - 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; et al. (Patterns, 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Arun Raja; Manan Dey; M Saiful Bari; Canwen Xu; et al. (ICLR, 2022)

A Fully Differentiable Set Autoencoder. - Nikita Janakarajan; Jannis Born; Matteo Manica (KDD, 2022)

PCfun: a hybrid computational framework for systematic characterization of protein complex function. - Varun S. Sharma; Andrea Fossati; Rodolfo Ciuffa; Marija Buljan; Evan G. Williams; Zhen Chen 009; Wenguang Shao; Patrick G. A. Pedrioli; Anthony W. Purcell; María Rodríguez Martínez; Jiangning Song; Matteo Manica; et al. (Briefings Bioinform., 2022)

Regression Transformer: Concurrent Conditional Generation and Regression by Blending Numerical and Textual Tokens. - Jannis Born; Matteo Manica (CoRR, 2022)

GT4SD: Generative Toolkit for Scientific Discovery. - 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; et al. (CoRR, 2022)

Z-BERT-A: a zero-shot Pipeline for Unknown Intent detection. - Daniele Comi; Dimitrios Christofidellis; Pier Francesco Piazza; Matteo Manica (CoRR, 2022)

Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model. - Jannis Born; Tien Huynh; Astrid Stroobants; Wendy D. Cornell; Matteo Manica (J. Chem. Inf. Model., 2022)

On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction. - Jannis Born; Yoel Shoshan; Tien Huynh; Wendy D. Cornell; Eric J. Martin; Matteo Manica (J. Chem. Inf. Model., 2022)

Zero-Shot-BERT-Adapters: a Zero-Shot Pipeline for Unknown Intent Detection. - Daniele Comi; Dimitrios Christofidellis; Pier Francesco Piazza; Matteo Manica (EMNLP (Findings), 2023)

Unifying Molecular and Textual Representations via Multi-task Language Modelling. - Dimitrios Christofidellis; Giorgio Giannone; Jannis Born; Ole Winther; Teodoro Laino; Matteo Manica (ICML, 2023)

Domain-agnostic and Multi-level Evaluation of Generative Models. - Girmaw Abebe Tadesse; Jannis Born; Celia Cintas; William Ogallo; Dmitry Zubarev; Matteo Manica; Komminist Weldemariam (CoRR, 2023)

Regression Transformer enables concurrent sequence regression and generation for molecular language modelling. - Jannis Born; Matteo Manica (Nat. Mac. Intell., 2023)

Integrating genetic algorithms and language models for enhanced enzyme design. - Yves Gaetan Nana Teukam; Federico Zipoli; Teodoro Laino; Emanuele Criscuolo; Francesca Grisoni; Matteo Manica (Briefings Bioinform., 2024)

Transforming the Hybrid Cloud for Emerging AI Workloads. - Deming Chen; Alaa Youssef; Ruchi Pendse; André Schleife; Bryan K. Clark; Hendrik F. Hamann; Jingrui He; Teodoro Laino; Lav R. Varshney; Yuxiong Wang; Avirup Sil; Reyhaneh Jabbarvand; et al. (CoRR, 2024)

Multiscale Byte Language Models - A Hierarchical Architecture for Causal Million-Length Sequence Modeling. - Eric Egli; Matteo Manica; Jannis Born (CoRR, 2025)

We Need Improved Data Curation and Attribution in AI for Scientific Discovery. - Mara Graziani; Antonio Foncubierta; Dimitrios Christofidellis; Irina Espejo Morales; Malina Molnar; Marvin Alberts; Matteo Manica; Jannis Born (CoRR, 2025)