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2020 – today
- 2023
[j11]Jannis Born
, Matteo Manica:
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling. Nat. Mac. Intell. 5(4): 432-444 (2023)- [c9]Daniele Comi, Dimitrios Christofidellis, Pier Francesco Piazza, Matteo Manica:
Zero-Shot-BERT-Adapters: a Zero-Shot Pipeline for Unknown Intent Detection. EMNLP (Findings) 2023: 650-663 - [c8]Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica:
Unifying Molecular and Textual Representations via Multi-task Language Modelling. ICML 2023: 6140-6157 - [i20]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 abs/2301.08750 (2023) - [i19]Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica:
Unifying Molecular and Textual Representations via Multi-task Language Modelling. CoRR abs/2301.12586 (2023) - 2022
- [j10]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) - [j9]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): 240-257 (2022) - [j8]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): 4295-4299 (2022) - [c7]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, 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 - [c6]Nikita Janakarajan, Jannis Born, Matteo Manica:
A Fully Differentiable Set Autoencoder. KDD 2022: 3061-3071 - [i18]Jannis Born, Matteo Manica:
Regression Transformer: Concurrent Conditional Generation and Regression by Blending Numerical and Textual Tokens. CoRR abs/2202.01338 (2022) - [i17]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 abs/2207.03928 (2022) - [i16]Daniele Comi, Dimitrios Christofidellis, Pier Francesco Piazza, Matteo Manica:
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detection. CoRR abs/2208.07084 (2022) - 2021
- [j7]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): 245-253 (2021) - [j6]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): 25024 (2021) - [j5]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): 100269 (2021) - [j4]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): 100330 (2021) - [c5]Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos, Hans Vandierendonck:
Understood in Translation: Transformers for Domain Understanding. SDU@AAAI 2021 - [i15]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 abs/2110.08207 (2021) - 2020
- [j3]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): W502-W508 (2020) - [j2]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): 2141-2147 (2020) - [c4]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: 7594-7601 - [c3]Emile Chapuis, Pierre Colombo, Matteo Manica, Matthieu Labeau, Chloé Clavel:
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog. EMNLP (Findings) 2020: 2636-2648 - [c2]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 - [c1]Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, María Rodríguez Martínez:
PaccMannRL: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. RECOMB 2020: 231-233 - [i14]Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, Chloé Clavel:
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction. CoRR abs/2002.08801 (2020) - [i13]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 abs/2002.09419 (2020) - [i12]Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, María Rodríguez Martínez:
PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models. CoRR abs/2005.13285 (2020) - [i11]Emile Chapuis, Pierre Colombo, Matteo Manica, Matthieu Labeau, Chloé Clavel:
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog. CoRR abs/2009.11152 (2020) - [i10]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 abs/2012.03084 (2020) - [i9]Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos, Hans Vandierendonck:
Understood in Translation, Transformers for Domain Understanding. CoRR abs/2012.10271 (2020)
2010 – 2019
- 2019
- [j1]Matteo Manica, Roland Mathis, Joris Cadow, María Rodríguez Martínez:
Context-specific interaction networks from vector representation of words. Nat. Mach. Intell. 1(4): 181-190 (2019) - [i8]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 abs/1901.06261 (2019) - [i7]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 abs/1904.11223 (2019) - [i6]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 abs/1907.08400 (2019) - [i5]Jannis Born, Matteo Manica, Ali Oskooei, María Rodríguez Martínez:
Reinforcement learning-driven de-novo design of anticancer compounds conditioned on biomolecular profiles. CoRR abs/1909.05114 (2019) - [i4]Matteo Manica, Ali Oskooei, Jannis Born:
AI Enables Explainable Drug Sensitivity Screenings. ERCIM News 2019(118) (2019) - 2018
- [b1]Matteo Manica:
Exploring Multi-Modal Learning Approaches Towards Precision Medicine. ETH Zurich, Zürich, Switzerland, 2018 - [i3]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 abs/1808.06603 (2018) - [i2]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 abs/1811.06802 (2018) - 2017
- [i1]Manuel Le Gallo, Abu Sebastian, Roland Mathis, Matteo Manica, Tomas Tuma, Costas Bekas, Alessandro Curioni, Evangelos Eleftheriou:
Mixed-Precision Memcomputing. CoRR abs/1701.04279 (2017)
Coauthor Index
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