| " What is relevant in a text document?": An interpretable machine learning approach L Arras, F Horn, G Montavon, KR Müller, W Samek PloS one 12 (8), e0181142, 2017 | 373 | 2017 |
| Robust artifactual independent component classification for BCI practitioners I Winkler, S Brandl, F Horn, E Waldburger, C Allefeld, M Tangermann Journal of neural engineering 11 (3), 035013, 2014 | 319 | 2014 |
| Predicting treatment response in social anxiety disorder from functional magnetic resonance imaging O Doehrmann, SS Ghosh, FE Polli, GO Reynolds, F Horn, A Keshavan, ... JAMA psychiatry 70 (1), 87-97, 2013 | 266 | 2013 |
| Explaining predictions of non-linear classifiers in NLP L Arras, F Horn, G Montavon, KR Müller, W Samek arXiv preprint arXiv:1606.07298, 2016 | 136 | 2016 |
| The autofeat Python Library for Automated Feature Engineering and Selection F Horn, R Pack, M Rieger Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019 | 83 | 2019 |
| Automating the search for a patent’s prior art with a full text similarity search L Helmers, F Horn, F Biegler, T Oppermann, KR Müller PloS one 14 (3), e0212103, 2019 | 62 | 2019 |
| Context encoders as a simple but powerful extension of word2vec F Horn Proceedings of the 2nd Workshop on Representation Learning for NLP, 10-14, 2017 | 31 | 2017 |
| Forecasting industrial aging processes with machine learning methods M Bogojeski, S Sauer, F Horn, KR Müller Computers & Chemical Engineering 144, 107123, 2021 | 21 | 2021 |
| Exploring text datasets by visualizing relevant words F Horn, L Arras, G Montavon, KR Müller, W Samek arXiv preprint arXiv:1707.05261, 2017 | 12 | 2017 |
| Discovering topics in text datasets by visualizing relevant words F Horn, L Arras, G Montavon, KR Müller, W Samek arXiv preprint arXiv:1707.06100, 2017 | 8 | 2017 |
| Predicting pairwise relations with neural similarity encoders F Horn, KR Müller Bulletin of the Polish Academy of Sciences: Technical Sciences, 2018 | 6 | 2018 |
| Interactive Exploration and Discovery of Scientific Publications with PubVis F Horn arXiv preprint arXiv:1706.08094, 2017 | 5 | 2017 |
| Exploring Word Usage Change with Continuously Evolving Embeddings F Horn Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 3 | 2021 |
| The DALPHI annotation framework & how its pre-annotations can improve annotator efficiency R Greinacher, F Horn arXiv preprint arXiv:1808.05558, 2018 | 3 | 2018 |
| Learning similarity preserving representations with neural similarity encoders F Horn, KR Müller arXiv preprint arXiv:1702.01824, 2017 | 3 | 2017 |
| Similarity encoder: A neural network architecture for learning similarity preserving embeddings F Horn Dissertation, Berlin, Technische Universität Berlin, 2020, 2020 | 1 | 2020 |
| Forecasting industrial aging processes with machine learning methods N Yakut, S Sauer, M Bogojeski, F Horn, K Mueller US Patent 11,860,617, 2024 | | 2024 |
| Predicting treatment response in social anxiety disorder from functional magnetic resonance imaging. JAMA Psychiatry, 70 (1), 87-97 O Doehrmann, SS Ghosh, FE Polli, GO Reynolds, F Horn, A Keshavan, ... | | 2013 |
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
