% % This file was created by the TYPO3 extension % bib % --- Timezone: CET % Creation date: 2024-03-28 % Creation time: 12-08-05 % --- Number of references % 18 % @Article { AmanovaME2024, title = {Finding the input features that reduce the entropy of a neural network’s prediction}, journal = {Applied Intelligence}, year = {2024}, month = {1}, day = {25}, tags = {8.4,8.42,ML}, DOI = {10.1007/s10489-024-05277-5}, author = {Amanova, N and Martin, J and Elster, C} } @Article { FallerAvME2023, title = {About the Generalizability of Deep Learning based Image Quality Assessment in Mammography}, journal = {Machine Learning: Science and Technology}, year = {2023}, month = {9}, day = {12}, tags = {8.4,8.42,ML}, state = {accepted}, DOI = {10.1088/2632-2153/acf914}, author = {Faller, J and Amanova, N and van Engen, R E and Martin, J and Elster, C} } @Article { MarschallWSE2023, title = {Machine learning based priors for Bayesian inversion in MR imaging}, journal = {Metrologia}, year = {2023}, month = {7}, day = {4}, volume = {60}, number = {4}, tags = {8.4,8.42,LargeScaleDataAna,ML}, DOI = {10.1088/1681-7575/ace3c2}, author = {Marschall, M and W{\"u}bbeler, G and Schm{\"a}hling, F and Elster, C} } @Article { BrahmaKMSK2023, title = {Data-efficient Bayesian learning for radial dynamic MR reconstruction}, journal = {Medical Physics}, year = {2023}, month = {6}, day = {27}, tags = {8.4,8.42,ML,Messunsicherheit,LargeScaleDataAna}, DOI = {10.1002/mp.16543}, author = {Brahma, S and Kolbitsch, C and Martin, J and Sch{\"a}ffter, T and Kofler, A} } @Article { MarschallWSE2022, title = {Generative models and Bayesian inversion using Laplace approximation}, journal = {Computational Statistics}, year = {2023}, month = {3}, day = {16}, tags = {8.4,8.42,ML,LargeScaleDataAna}, DOI = {10.1007/s00180-023-01345-5}, author = {Marschall, M and W{\"u}bbeler, G and Schm{\"a}hling, F and Elster, C} } @Article { MartinE2021_2, title = {Errors-in-Variables for deep learning: rethinking aleatoric uncertainty}, journal = {Neural Processing Letters}, year = {2022}, month = {11}, day = {1}, tags = {8.4,8.42,ML}, ISSN = {1573-773X}, DOI = {10.1007/s11063-022-11066-3}, author = {Martin, J and Elster, C} } @Article { OlbrichRKLvBOS2022, title = {Deep learning based liquid level extraction from video observations of gas-liquid flows}, journal = {International Journal of Multiphase Flow}, year = {2022}, month = {9}, day = {10}, tags = {8.4,8.41,Flow,ML}, DOI = {https://doi.org/10.1016/j.ijmultiphaseflow.2022.104247}, author = {Olbrich, M. and Riazy, L. and Kretz, T. and Leonard, T. and van Putten, D.S. and B{\"a}r, M. and Oberleithner, K. and Schmelter, S.} } @Phdthesis { HarrenneeHoffmann2022, title = {Investigating deep ensembles for the tilted-wave interferometer}, year = {2022}, month = {8}, day = {15}, keywords = {publiziert}, tags = {8.4,8.42,ML,Form}, url = {https://depositonce.tu-berlin.de/bitstream/11303/17264/4/harren_lara.pdf}, school = {TU Berlin}, type = {PhD Thesis}, DOI = {10.14279/depositonce-16044}, author = {Harren n{\'e}e Hoffmann, L} } @Article { SchmahlingME2021, title = {A framework for benchmarking uncertainty in deep regression}, journal = {Applied Intelligence}, year = {2022}, month = {8}, day = {9}, tags = {8.4,8.42,ML}, DOI = {10.1007/s10489-022-03908-3}, author = {Schm{\"a}hling, Franko and Martin, J{\"o}rg and Elster, Clemens} } @Article { AmanovaME2022, title = {Explainability for deep learning in mammography image quality assessment}, journal = {Machine Learning: Science and Technology}, year = {2022}, month = {6}, day = {17}, tags = {8.4,8.42,ML}, state = {accepted}, DOI = {10.1088/2632-2153/ac7a03}, author = {Amanova, N and Martin, J and Elster, C} } @Article { MehariS2021, title = {Self-supervised representation learning from 12-lead ECG data}, journal = {Computers in Biology and Medicine}, year = {2021}, month = {12}, day = {18}, volume = {141}, pages = {105114}, tags = {8.4,8.41,ML}, DOI = {https://doi.org/10.1016/j.compbiomed.2021.105114}, author = {Mehari, T and Strodthoff, N} } @Article { HoffmannFE2021_2, title = {Deep learning for tilted-wave interferometry}, journal = {tm - Technisches Messen}, year = {2021}, month = {11}, day = {20}, keywords = {publiziert}, tags = {8.4,8.42,Form,ML}, DOI = {10.1515/teme-2021-0103}, author = {Hoffmann, L and Fortmeier, I and Elster, C} } @Article { HoffmannFE2021, title = {Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements}, journal = {Machine Learning: Science and Technology}, year = {2021}, month = {5}, day = {24}, keywords = {publiziert}, tags = {8.4,8.42,ML,Form}, DOI = {10.1088/2632-2153/ac0495}, author = {Hoffmann, L and Fortmeier, I and Elster, C} } @Article { MartinE2020_3, title = {Detecting unusual input to neural networks}, journal = {Appl Intell}, year = {2020}, month = {10}, day = {30}, keywords = {publiziert}, tags = {8.4,8.42,ML}, DOI = {10.1007/s10489-020-01925-8}, author = {Martin, J and Elster, C} } @Phdthesis { Kretz2020, title = {Development of model observers for quantitative assessment of mammography image quality}, year = {2020}, month = {10}, day = {7}, keywords = {publiziert}, tags = {8.4,8.42,ML}, url = {http://dx.doi.org/10.14279/depositonce-10552}, school = {TU Berlin}, type = {PhD Thesis}, author = {Kretz, T} } @Article { HoffmannE2020, title = {Deep Neural Networks for Computational Optical Form Measurements}, journal = {Journal of Sensors and Sensor Systems}, year = {2020}, month = {9}, day = {24}, volume = {9}, pages = {301--307}, keywords = {publiziert}, tags = {8.4,8.42,ML,Form}, DOI = {10.5194/jsss-9-301-2020}, author = {Hoffmann, L and Elster, C} } @Article { KretzMSE2020, title = {Mammography Image Quality Assurance Using Deep Learning}, journal = {IEEE Transactions on Biomedical Engineering}, year = {2020}, month = {4}, day = {14}, keywords = {publiziert}, tags = {8.4,8.42,ML}, DOI = {10.1109/TBME.2020.2983539}, author = {Kretz, T and M{\"u}ller, K-R and Sch{\"a}ffter, T and Elster, C} } @Article { MartinE2020, title = {Inspecting adversarial examples using the fisher information}, journal = {Neurocomputing}, year = {2020}, month = {3}, day = {21}, volume = {382}, pages = {80--86}, keywords = {publiziert}, tags = {8.4,8.42,ML}, DOI = {10.1016/j.neucom.2019.11.052}, author = {Martin, J and Elster, C} }