@article {679,
	title = {Bayesian Calibration of MEMS Accelerometers},
	journal = {IEEE Sensors Journal},
	year = {2023},
	author = {D{\"u}rr, Oliver and Fan, Po-Yu and Yin, Zong-Xian}
}
@article {680,
	title = {Deep transformation models for functional outcome prediction after acute ischemic stroke},
	journal = {Biometrical Journal},
	volume = {65},
	year = {2023},
	pages = {2100379},
	author = {Herzog, Lisa and Kook, Lucas and G{\"o}tschi, Andrea and Petermann, Katrin and H{\"a}nsel, Martin and Hamann, Janne and D{\"u}rr, Oliver and Wegener, Susanne and Sick, Beate}
}
@article {682,
	title = {Novel AI-Based Algorithm for the Automated Computation of Coronal Parameters in Adolescent Idiopathic Scoliosis Patients: A Validation Study on 100 Preoperative Full Spine X-Rays},
	journal = {Global Spine Journal},
	year = {2023},
	pages = {21925682231154543},
	author = {Berlin, Clara and Adomeit, Sonja and Grover, Priyanka and Dreischarf, Marcel and Halm, Henry and D{\"u}rr, Oliver and Obid, Peter}
}
@article {681,
	title = {Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows},
	journal = {IEEE Transactions on Smart Grid},
	year = {2023},
	author = {Arpogaus, Marcel and Voss, Marcus and Sick, Beate and Nigge-Uricher, Mark and D{\"u}rr, Oliver}
}
@article {683,
	title = {140. Automated measurement technique for coronal parameters using a novel artificial intelligence algorithm: an independent validation study on 100 preoperative AP spine X-rays},
	journal = {The Spine Journal},
	volume = {22},
	year = {2022},
	pages = {S74},
	author = {Berlin, Clara and Adomeit, Sonja and Grover, Priyanka and Dreischarf, Marcel and D{\"u}rr, Oliver and Obid, Peter}
}
@article {684,
	title = {Deep and interpretable regression models for ordinal outcomes},
	journal = {Pattern Recognition},
	volume = {122},
	year = {2022},
	pages = {108263},
	author = {Kook, Lucas and Herzog, Lisa and Hothorn, Torsten and D{\"u}rr, Oliver and Sick, Beate}
}
@article {685,
	title = {Validation study of an algorithm based on artificial intelligence for automated computation of coronal parameters on preoperative AP X-rays},
	journal = {Brain and Spine},
	volume = {2},
	year = {2022},
	pages = {101156},
	author = {Adomeit, Sonja and Berlin, Clara and Grover, Priyanka and Dreischarf, Marcel and Halm, Henry and D{\"u}rr, Oliver and Obid, Peter}
}
@conference {686,
	title = {Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations},
	booktitle = {2021 International Conference on Data Mining Workshops (ICDMW)},
	year = {2021},
	pages = {398{\textendash}404},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Scharpf, Philipp and Hong, Chi Lap and D{\"u}rr, Oliver}
}
@conference {624,
	title = {Deep transformation models: Tackling complex regression problems with neural network based transformation models},
	booktitle = {Accepted for Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan/Online, 2021},
	year = {2021},
	author = {Sick, Beate and Hothorn, Torsten and D{\"u}rr, Oliver}
}
@conference {687,
	title = {Probabilistic short-term low-voltage load forecasting using bernstein-polynomial normalizing flows},
	booktitle = {ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual},
	year = {2021},
	author = {Arpogaus, Marcel and Vo{\ss}, Marcus and Sick, Beate and Nigge-Uricher, Mark and D{\"u}rr, Oliver}
}
@article {623,
	title = {Integrating uncertainty in deep neural networks for MRI based stroke analysis},
	journal = {Medical Image Analysis},
	volume = {65},
	year = {2020},
	pages = {101790},
	author = {Herzog, Lisa and Murina, Elvis and D{\"u}rr, Oliver and Wegener, Susanne and Sick, Beate}
}
@book {688,
	title = {Probabilistic deep learning: With python, keras and tensorflow probability},
	year = {2020},
	publisher = {Manning Publications},
	organization = {Manning Publications},
	author = {D{\"u}rr, Oliver and Sick, Beate and Murina, Elvis}
}
@inbook {614,
	title = {Beyond ImageNet: Deep Learning in Industrial Practice},
	booktitle = {Applied Data Science},
	year = {2019},
	pages = {205-232},
	publisher = {Springer},
	organization = {Springer},
	isbn = {978-3-030-11820-4},
	issn = {978-3-030-11821-1},
	doi = {https://doi.org/10.1007/978-3-030-11821-1_12},
	url = {https://link.springer.com/chapter/10.1007\%2F978-3-030-11821-1_12},
	author = {Stadelmann, Thilo and Tolkachev, Vasily and Sick, Beate and D{\"u}rr, Oliver}
}
@article {613,
	title = {Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks},
	year = {2019},
	url = {https://www.journals.elsevier.com/computers-and-electrical-engineering},
	author = {Rohrbach, Janick and Rainhard, Tobias and Sick, Beate and D{\"u}rr, Oliver}
}
@conference {616,
	title = {Automatic classification of non-small cell lung cancer histologic sub-types by deep learning},
	booktitle = {VIRCHOWS ARCHIV},
	year = {2018},
	month = {09/18},
	pages = {108-108},
	publisher = {Springer},
	organization = {Springer},
	author = {Casanova, R and Murina, Elvis and Haberecker, M and Honcharova-Biletska, H and Vrugt, B and D{\"u}rr, Oliver and Sick, Beate and Soltermann, A}
}
@conference {stadelmann2018capturing,
	title = {Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering},
	booktitle = {IAPR Workshop on Artificial Neural Networks in Pattern Recognition},
	year = {2018},
	pages = {333{\textendash}345},
	publisher = {Springer},
	organization = {Springer},
	url = {https://www.springerprofessional.de/capturing-suprasegmental-features-of-a-voice-with-rnns-for-impro/16083698}
}
@article {593,
	title = {Developing deep learning applications for life science and pharma industry},
	journal = {Drug research},
	volume = {68},
	year = {2018},
	pages = {305{\textendash}310},
	doi = {https://doi.org/10.1055/s-0043-124761},
	url = {https://doi.org/10.1055/s-0043-124761},
	author = {Siegismund, Daniel and Tolkachev, Vasily and Heyse, Stephan and Sick, Beate and D{\"u}rr, Oliver and Steigele, Stephan}
}
@article {durr2018know,
	title = {Know When You Don{\textquoteright}t Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes},
	journal = {Assay and drug development technologies},
	volume = {16},
	number = {6},
	year = {2018},
	pages = {343{\textendash}349},
	publisher = {Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA},
	url = {https://www.liebertpub.com/doi/10.1089/adt.2018.859}
}
@conference {meier2018learning,
	title = {Learning Neural Models for End-to-End Clustering},
	booktitle = {IAPR Workshop on Artificial Neural Networks in Pattern Recognition},
	year = {2018},
	pages = {126{\textendash}138},
	publisher = {Springer},
	organization = {Springer},
	doi = {https://doi.org/10.1007/978-3-319-99978-4_10},
	url = {https://link.springer.com/chapter/10.1007\%2F978-3-319-99978-4_10}
}
@conference {lukic2017learning,
	title = {Learning embeddings for speaker clustering based on voice equality},
	booktitle = {Machine Learning for Signal Processing (MLSP), 2017 IEEE 27th International Workshop on},
	year = {2017},
	pages = {1{\textendash}6},
	publisher = {IEEE},
	organization = {IEEE}
}
@article {durr2016single,
	title = {Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks},
	journal = {Journal of biomolecular screening},
	volume = {21},
	number = {9},
	year = {2016},
	pages = {998{\textendash}1003},
	publisher = {SAGE Publications},
	doi = {https://doi.org/10.1177/1087057116631284},
	url = {https://doi.org/10.1177/1087057116631284}
}
@conference {lukic2016speaker,
	title = {Speaker Identification and Clustering using Convolution Neural Networks},
	booktitle = {IEEE International workshop on Machine Learning for Signal Processing},
	year = {2016}
}
@conference {durr2015deep,
	title = {Deep Learning on a Raspberry Pi for Real Time Face Recognition.},
	booktitle = {Eurographics (Posters)},
	year = {2015},
	pages = {11{\textendash}12}
}
@article {franzini2015gene,
	title = {Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced non-squamous non-small cell lung cancer patients (SAKK 19/05 trial)},
	journal = {Clinical Cancer Research},
	year = {2015},
	pages = {clincanres{\textendash}{\textendash}3135},
	publisher = {American Association for Cancer Research}
}
@conference {durr2014joint_forces,
	title = {JOINT{\_}FORCES: Unite Competing Sentiment Classifiers with Random Forest.},
	booktitle = {SemEval@ COLING},
	year = {2014},
	pages = {366{\textendash}369}
}
@conference {cieliebak2014meta,
	title = {Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools.},
	booktitle = {Language Resources and Evaluation Conference (LREC)},
	year = {2014},
	pages = {3100{\textendash}3104}
}
@article {franzini2014tumor,
	title = {Tumor-associated stromal gene expression signatures predict therapeutic response to erlotinib/bevacizumab in non-small cell lung cancer (NSCLC)},
	journal = {European Respiratory Journal},
	volume = {44},
	number = {Suppl 58},
	year = {2014},
	pages = {P821},
	publisher = {Eur Respiratory Soc}
}
@conference {cieliebak2013potential,
	title = {Potential and Limitations of Commercial Sentiment Detection Tools.},
	booktitle = {ESSEM@ AI* IA},
	year = {2013},
	pages = {47{\textendash}58},
	publisher = {Citeseer},
	organization = {Citeseer}
}
@article {durr2012using,
	title = {Using Community Structure for Complex Network Layout},
	journal = {arXiv preprint arXiv:1207.6282},
	year = {2012}
}
@article {durr2007robust,
	title = {Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay},
	journal = {Journal of biomolecular screening},
	volume = {12},
	number = {8},
	year = {2007},
	pages = {1042{\textendash}1049},
	publisher = {Sage Publications Sage CA: Los Angeles, CA}
}
@mastersthesis {durr2003theoretical,
	title = {Theoretical Studies of Relaxation and Ionic Transport in Polymers},
	number = {January 2003},
	year = {2003},
	type = {phd},
	isbn = {3898255859},
	url = {http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-10270}
}
@article {durr2002effective,
	title = {Effective medium theory of conduction in stretched polymer electrolytes},
	journal = {arXiv preprint cond-mat/0202165},
	year = {2002}
}
@article {durr1998monte,
	title = {Monte-carlo-simulationen zu polymeren ionenleitern},
	year = {1998}
}
