| From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge P Bandi, O Geessink, Q Manson, M Van Dijk, M Balkenhol, M Hermsen, ... IEEE transactions on medical imaging 38 (2), 550-560, 2018 | 577 | 2018 |
| Sample-Efficient Automated Deep Reinforcement Learning JKH Franke, G Köhler, A Biedenkapp, F Hutter Proceedings of Conference on Learning Representations. ICLR 2021., 2020 | 46 | 2020 |
| Phoneme Boundary Detection using Deep Bidirectional LSTMs J Franke, M Mueller, F Hamlaoui, S Stueker, A Waibel Speech Communication; 12. ITG Symposium; Proceedings of, 1-5, 2016 | 42 | 2016 |
| Robust and scalable differentiable neural computer for question answering J Franke, J Niehues, A Waibel Proceedings of the Workshop on Machine Reading for Question Answering. ACL 2018., 2018 | 28 | 2018 |
| Towards phoneme inventory discovery for documentation of unwritten languages M Müller, J Franke, A Waibel, S Stüker Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International …, 2017 | 17 | 2017 |
| Improving phoneme set discovery for documenting unwritten languages M Müller, J Franke, S Stüker, A Waibe Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung …, 2017 | 14 | 2017 |
| Why do machine learning practitioners still use manual tuning? A qualitative study N Hasebrook, F Morsbach, N Kannengießer, J Franke, F Hutter, ... arXiv preprint arXiv:2203.01717, 2022 | 13 | 2022 |
| Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design JKH Franke, F Runge, F Hutter 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022 | 10 | 2022 |
| Hyperparameter Transfer Across Developer Adjustments D Stoll, JKH Franke, D Wagner, S Selg, F Hutter NeurIPS 4th Workshop on Meta-Learning (2020), 2020 | 9 | 2020 |
| Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control JKH Franke, G Köhler, N Awad, F Hutter Workshop on Meta-Learning. NeurIPS 2019., 2019 | 8 | 2019 |
| Scalable Deep Learning for RNA Secondary Structure Prediction JKH Franke, F Runge, F Hutter The 2023 ICML Workshop on Computational Biology, ICML 2023, 2023 | 7 | 2023 |
| Rnabench: A comprehensive library for in silico rna modelling F Runge, K Farid, JKH Franke, F Hutter bioRxiv, 2024.01. 09.574794, 2024 | 4 | 2024 |
| Practitioner motives to select hyperparameter optimization methods N Hasebrook, F Morsbach, N Kannengießer, M Zöller, J Franke, ... arXiv preprint arXiv:2203.01717, 2022 | 4 | 2022 |
| Partial RNA design F Runge, J Franke, D Fertmann, R Backofen, F Hutter Bioinformatics 40 (Supplement_1), i437-i445, 2024 | 2 | 2024 |
| RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction JKH Franke, F Runge, R Koeksal, R Backofen, F Hutter bioRxiv, 2024.02. 12.579881, 2024 | 2 | 2024 |
| Rethinking performance measures of rna secondary structure problems F Runge, JKH Franke, D Fertmann, F Hutter arXiv preprint arXiv:2401.05351, 2023 | 2 | 2023 |
| Constrained Parameter Regularization JKH Franke, M Hefenbrock, G Koehler, F Hutter | 2 | 2023 |
| HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models RS Sukthanker, A Zela, B Staffler, JKH Franke, F Hutter arXiv preprint arXiv:2405.10299, 2024 | 1 | 2024 |
| Towards Automated Design of Riboswitches F Runge, JKH Franke, F Hutter The 2023 ICML Workshop on Computational Biology, ICML 2023, 2023 | 1 | 2023 |
| Fast Optimizer Benchmark S Blauth, T Bürger, Z Häringer, J Franke, F Hutter arXiv preprint arXiv:2406.18701, 2024 | | 2024 |
Frank HutterELLIS Institute & Professor, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
