| Nlprolog: Reasoning with weak unification for question answering in natural language L Weber, P Minervini, J Münchmeyer, U Leser, T Rocktäschel arXiv preprint arXiv:1906.06187, 2019 | 83 | 2019 |
| HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition L Weber, M Sänger, J Münchmeyer, M Habibi, U Leser, A Akbik Bioinformatics 37 (17), 2792-2794, 2021 | 53 | 2021 |
| HUNER: improving biomedical NER with pretraining L Weber, J Münchmeyer, T Rocktäschel, M Habibi, U Leser Bioinformatics 36 (1), 295-302, 2020 | 41 | 2020 |
| The transformer earthquake alerting model: A new versatile approach to earthquake early warning J Münchmeyer, D Bindi, U Leser, F Tilmann Geophysical Journal International 225 (1), 646-656, 2021 | 31 | 2021 |
| Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers J Münchmeyer, J Woollam, A Rietbrock, F Tilmann, D Lange, T Bornstein, ... Journal of Geophysical Research: Solid Earth 127 (1), e2021JB023499, 2022 | 28 | 2022 |
| Earthquake magnitude and location estimation from real time seismic waveforms with a transformer network J Münchmeyer, D Bindi, U Leser, F Tilmann Geophysical Journal International 226 (2), 1086-1104, 2021 | 27 | 2021 |
| SeisBench—A toolbox for machine learning in seismology J Woollam, J Münchmeyer, F Tilmann, A Rietbrock, D Lange, T Bornstein, ... Seismological Society of America 93 (3), 1695-1709, 2022 | 16 | 2022 |
| Estimating genome-wide regulatory activity from multi-omics data sets using mathematical optimization S Trescher, J Münchmeyer, U Leser BMC systems biology 11, 1-18, 2017 | 14 | 2017 |
| Low uncertainty multifeature magnitude estimation with 3-D corrections and boosting tree regression: application to North Chile J Münchmeyer, D Bindi, C Sippl, U Leser, F Tilmann Geophysical Journal International 220 (1), 142-159, 2020 | 11 | 2020 |
| Extend, don’t rebuild: Phrasing conditional graph modification as autoregressive sequence labelling L Weber, J Münchmeyer, S Garda, U Leser Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 3 | 2021 |
| Machine learning identifies ecological selectivity patterns across the end-Permian mass extinction WJ Foster, G Ayzel, J Münchmeyer, T Rettelbach, NH Kitzmann, TT Isson, ... Paleobiology 48 (3), 357-371, 2022 | 2 | 2022 |
| Fast earthquake assessment and earthquake early warning dataset for Italy J Münchmeyer, D Bindi, U Leser, F Tilmann GFZ Data Services, 2020 | 2 | 2020 |
| A probabilistic view on rupture predictability: All earthquakes evolve similarly J Münchmeyer, U Leser, F Tilmann Geophysical Research Letters 49 (13), e2022GL098344, 2022 | 1 | 2022 |
| Graph neural networks for learning molecular excitation spectra K Singh, J Münchmeyer, L Weber, U Leser, A Bande Journal of Chemical Theory and Computation 18 (7), 4408-4417, 2022 | 1 | 2022 |
| Fast earthquake assessment dataset for chile J Münchmeyer, D Bindi, U Leser, F Tilmann GFZ Data Services, 2021 | 1 | 2021 |
| Team–the transformer earthquake alerting model J Münchmeyer, D Bindi, U Leser, F Tilmann GFZ Data Services, 2021 | 1 | 2021 |
| Phase Picking on OBS Data with Deep Learning: Bringing SeisBench to the Ocean Bottom J Münchmeyer, T Bornstein, D Lange, J Woollam, A Rietbrock, ... Fall Meeting 2022, 2022 | | 2022 |
| Machine-Learning-Based Earthquake Monitoring and Seismic Analysis III Poster M Zhang, W Zhu, IW McBrearty, J Münchmeyer Fall Meeting 2022, 2022 | | 2022 |
| Convolutional event embeddings for fast probabilistic earthquake assessment J Münchmeyer, D Bindi, U Leser, F Tilmann Authorea Preprints, 2022 | | 2022 |
| Machine learning for fast and accurate assessment of earthquake source parameters J Münchmeyer Humboldt-Universität zu Berlin, 2022 | | 2022 |
Ulf LeserKnowledge Management in Bioinformatics, Humboldt-Universität zu BerlinVerified email at informatik.hu-berlin.de
