| Towards automated auditing with machine learning R Sifa, A Ladi, M Pielka, R Ramamurthy, L Hillebrand, B Kirsch, D Biesner, ... Proceedings of the ACM Symposium on Document Engineering 2019, 1-4, 2019 | 43 | 2019 |
| Anonymization of German financial documents using neural network-based language models with contextual word representations D Biesner, R Ramamurthy, R Stenzel, M Lübbering, L Hillebrand, A Ladi, ... International Journal of Data Science and Analytics, 1-11, 2022 | 29 | 2022 |
| From imbalanced classification to supervised outlier detection problems: adversarially trained auto encoders M Lübbering, R Ramamurthy, M Gebauer, T Bell, R Sifa, C Bauckhage Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020 | 8 | 2020 |
| Decoupling autoencoders for robust one-vs-rest classification M Lübbering, M Gebauer, R Ramamurthy, C Bauckhage, R Sifa 2021 IEEE 8th International Conference on Data Science and Advanced …, 2021 | 6 | 2021 |
| Utilizing Representation Learning for Robust Text Classification Under Datasetshift. M Lübbering, M Gebauer, R Ramamurthy, M Pielka, C Bauckhage, R Sifa LWDA, 157-162, 2021 | 6 | 2021 |
| Knowledge graph based question answering system for financial securities M Bulla, L Hillebrand, M Lübbering, R Sifa KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI …, 2021 | 6 | 2021 |
| Supervised autoencoder variants for end to end anomaly detection M Lübbering, M Gebauer, R Ramamurthy, R Sifa, C Bauckhage Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 6 | 2021 |
| Towards symmetry-aware pneumonia detection on chest x-rays H Schneider, M Lübbering, R Kador, M Broß, P Priya, D Biesner, B Wulff, ... 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 543-550, 2022 | 5 | 2022 |
| Tokenizer Choice For LLM Training: Negligible or Crucial? M Ali, M Fromm, K Thellmann, R Rutmann, M Lübbering, J Leveling, ... arXiv preprint arXiv:2310.08754, 2023 | 4 | 2023 |
| Bounding open space risk with decoupling autoencoders in open set recognition M Lübbering, M Gebauer, R Ramamurthy, C Bauckhage, R Sifa International Journal of Data Science and Analytics 14 (4), 351-373, 2022 | 4 | 2022 |
| A clustering backed deep learning approach for document layout analysis R Agombar, M Luebbering, R Sifa Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG …, 2020 | 4 | 2020 |
| Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis. M Lübbering, M Pielka, K Das, M Gebauer, R Ramamurthy, C Bauckhage, ... ESANN, 2021 | 3 | 2021 |
| Novelty-guided reinforcement learning via encoded behaviors R Ramamurthy, R Sifa, M Lübbering, C Bauckhage 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 3 | 2020 |
| Towards supervised extractive text summarization via RNN-based sequence classification E Brito, M Lübbering, D Biesner, LP Hillebrand, C Bauckhage arXiv preprint arXiv:1911.06121, 2019 | 3 | 2019 |
| Datastack: unification of heterogeneous machine learning dataset interfaces M Lübbering, M Pielka, I Henk, R Sifa 2022 IEEE 38th International Conference on Data Engineering Workshops (ICDEW …, 2022 | 2 | 2022 |
| Automatic indexing of financial documents via information extraction R Ramamurthy, M Lübbering, T Bell, M Gebauer, B Ulusay, ... 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-05, 2021 | 2 | 2021 |
| Leveraging Contextual Text Representations for Anonymizing German Financial Documents D Biesner, R Ramamurthy, M Lübbering, B Fürst, H Ismail, L Hillebrand, ... Proc. Knowledge Discovery from Unstructured Data in Financial Services. AAAI, 2020 | 2 | 2020 |
| From open set recognition towards robust multi-class classification M Lübbering, M Gebauer, R Ramamurthy, C Bauckhage, R Sifa International Conference on Artificial Neural Networks, 643-655, 2022 | 1 | 2022 |
| Guided Reinforcement Learning via Sequence Learning R Ramamurthy, R Sifa, M Lübbering, C Bauckhage Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020 | 1 | 2020 |
| What company does my news article refer to? Tackling multiclass problems with topic modeling M Lübbering, J Kunkel, P Farrell Berlin: Weierstraß-Institut für Angewandte Analysis und Stochastik, 2019 | 1 | 2019 |
Rafet SifaProfessor of Applied Machine Learning at University of Bonn and Fraunhofer IAISVerified email at iais.fraunhofer.de
