Jannis Born

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 29

Top Topics

Ultrasound Imaging

Reinforcement Learning

Top Venues

J. Chem. Inf. Model.

Publications

Nicola Mariella, Albert Akhriev, Francesco Tacchino, Christa Zoufal, Juan Carlos Gonzalez-Espitia, Benedek Harsanyi, Eugene Koskin, Ivano Tavernelli, Stefan Woerner, Marianna Rapsomaniki, Sergiy Zhuk, Jannis Born
Quantum Theory and Application of Contextual Optimal Transport. CoRR (2024)
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)
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
Unifying Molecular and Textual Representations via Multi-task Language Modelling. ICML (2023)
Nikita Janakarajan, Tim Erdmann, Sarath Swaminathan, Teodoro Laino, Jannis Born
Language models in molecular discovery. CoRR (2023)
Jannis Born, Nikola I. Nikolov, Anna Rosenkranz, Alfred Schabmann, Barbara Maria Schmidt
A computational investigation of inventive spelling and the "Lesen durch Schreiben" method. Comput. Educ. Artif. Intell. 3 (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)
Maria Gabrani, Ender Konukoglu, David Beymer, Gustavo Carneiro, Jannis Born, Michal Guindy, Michal Rosen-Zvi
Lessons Learned from the Development and Application of Medical Imaging-Based AI Technologies for Combating COVID-19: Why Discuss, What Next. CLIP/DCL/LL-COVID19/PPML@MICCAI (2021)
Anna Weber, Jannis Born, María Rodríguez Martínez
TITAN: T-cell receptor specificity prediction with bimodal attention networks. 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)
Anna Weber, Jannis Born, María Rodríguez Martínez
TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networks. 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)
Anwaar Ulhaq, Jannis Born, Asim Khan, Douglas P. S. Gomes, Subrata Chakraborty, Manoranjan Paul
COVID-19 Control by Computer Vision Approaches: A Survey. IEEE Access 8 (2020)
Jannis Born, Nina Wiedemann, Gabriel Brändle, Charlotte Buhre, Bastian Rieck, Karsten M. Borgwardt
Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis. CoRR (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)
Jannis Born, Gabriel Brändle, Manuel Cossio, Marion Disdier, Julie Goulet, Jérémie Roulin, Nina Wiedemann
POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS). 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)
Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, María Rodríguez Martínez
: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. RECOMB (2020)
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, Ali Oskooei, Jannis Born
AI Enables Explainable Drug Sensitivity Screenings. ERCIM News 2019 (118) (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)