@article {700,
	title = {Preventing Parasitic Learning in Online Identification of Building RC Thermal Models: A Stochastic-Volatility Rao{\textendash}Blackwellized Particle Filter},
	year = {2026},
	doi = {10.2139/ssrn.6017847},
	url = {http://dx.doi.org/10.2139/ssrn.6017847},
	author = {Ramadane, Mohamed and Bohnet, Doris}
}
@conference {697,
	title = {Assessing the Environmental Impact of IoT Devices - Hotspots and Guidelines for a Better Understanding},
	booktitle = {2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC)},
	year = {2025},
	pages = {1{\textendash}11},
	publisher = {IEEE},
	organization = {IEEE},
	doi = {10.1109/ice/itmc65658.2025.11106638},
	url = {http://dx.doi.org/10.1109/ice/itmc65658.2025.11106638},
	author = {Baumgartner, Corinna and Bohnet, Doris and Meyer, Sonja and Leber, Angelika and Ramadane, Mohamed}
}
@conference {699,
	title = {Dynamic Use-Phase Variability In IoT-Enabled Systems: A Simulation-Based Case Study Of Smart Thermostats},
	booktitle = {ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita},
	year = {2025},
	pages = {711{\textendash}717},
	publisher = {ECMS},
	organization = {ECMS},
	doi = {10.7148/2025-0711},
	url = {http://dx.doi.org/10.7148/2025-0711},
	author = {Ramadane, Mohamed and Bohnet, Doris}
}
@conference {694,
	title = {Paths and Ambient Spaces in Neural Loss Landscapes},
	booktitle = {Proceedings of The 28th International Conference on Artificial Intelligence and Statistics},
	year = {2025},
	month = {03{\textendash}05 May},
	pages = {10{\textendash}18},
	publisher = {PMLR},
	organization = {PMLR},
	abstract = {Understanding the structure of neural network loss surfaces, particularly the emergence of low-loss tunnels, is critical for advancing neural network theory and practice. In this paper, we propose a novel approach to directly embed loss tunnels into the loss landscape of neural networks. Exploring the properties of these loss tunnels offers new insights into their length and structure and sheds light on some common misconceptions. We then apply our approach to Bayesian neural networks, where we improve subspace inference by identifying pitfalls and proposing a more natural prior that better guides the sampling procedure.},
	url = {https://proceedings.mlr.press/v258/dold25a.html},
	author = {Dold, Daniel and Kobialka, Julius and Palm, Nicolai and Sommer, Emanuel and R{\"u}gamer, David and D{\"u}rr, Oliver},
	editor = {Li, Yingzhen and Mandt, Stephan and Agrawal, Shipra and Khan, Emtiyaz}
}
@conference {691,
	title = {Solgenia{\textemdash}A test vessel toward energy-efficient autonomous water taxi applications},
	booktitle = {Ocean Engineering},
	year = {2025},
	doi = {https://doi.org/10.1016/j.oceaneng.2025.121011},
	url = {https://www.sciencedirect.com/science/article/pii/S0029801825007243},
	author = {Hannes Homburger and Stefan Wirtensohn and Patrick Hoher and Tim Baur and Dennis Griesser and Moritz Diehl and Johannes Reuter}
}
@conference {690,
	title = {3D-Extended Object Tracking and Shape Classification with a Lidar Sensor using Random Matrices and Virtual Measurement Models},
	booktitle = {27th International Conference on Information Fusion (FUSION)},
	year = {2024},
	pages = {1-8},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Venice, Italy},
	doi = {10.23919/FUSION59988.2024.10706411},
	author = {Patrick Hoher and Tim Baur and Johannes Reuter and Dennis Griesser and Felix Govaers and Wolfgang Koch}
}
@conference {693,
	title = {Bayesian Semi-structured Subspace Inference},
	booktitle = {Proceedings of The 27th International Conference on Artificial Intelligence and Statistics},
	year = {2024},
	month = {02{\textendash}04 May},
	pages = {1819{\textendash}1827},
	publisher = {PMLR},
	organization = {PMLR},
	abstract = {Semi-structured regression models enable the joint modeling of interpretable structured and complex unstructured feature effects. The structured model part is inspired by statistical models and can be used to infer the input-output relationship for features of particular importance. The complex unstructured part defines an arbitrary deep neural network and thereby provides enough flexibility to achieve competitive prediction performance. While these models can also account for aleatoric uncertainty, there is still a lack of work on accounting for epistemic uncertainty. In this paper, we address this problem by presenting a Bayesian approximation for semi-structured regression models using subspace inference. To this end, we extend subspace inference for joint posterior sampling from a full parameter space for structured effects and a subspace for unstructured effects. Apart from this hybrid sampling scheme, our method allows for tunable complexity of the subspace and can capture multiple minima in the loss landscape. Numerical experiments validate our approach{\textquoteright}s efficacy in recovering structured effect parameter posteriors in semi-structured models and approaching the full-space posterior distribution of MCMC for increasing subspace dimension. Further, our approach exhibits competitive predictive performance across simulated and real-world datasets.},
	url = {https://proceedings.mlr.press/v238/dold24a.html},
	author = {Dold, Daniel and Ruegamer, David and Sick, Beate and D{\"u}rr, Oliver},
	editor = {Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen}
}
@article {696,
	title = {Environmental Impact Assessment of IoT Devices: A Graph-based Approach},
	journal = {Procedia Computer Science},
	volume = {236},
	year = {2024},
	pages = {338{\textendash}347},
	issn = {1877-0509},
	doi = {10.1016/j.procs.2024.05.039},
	url = {http://dx.doi.org/10.1016/j.procs.2024.05.039},
	author = {Ramadane, Mohamed and Meyer, Sonja and Bohnet, Doris}
}
@article {706,
	title = {Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo},
	journal = {Journal of Statistical Software},
	volume = {111},
	year = {2024},
	issn = {1548-7660},
	doi = {10.18637/jss.v111.i10},
	url = {http://dx.doi.org/10.18637/jss.v111.i10},
	author = {Kook, Lucas and Baumann, Philipp F. M. and D{\"u}rr, Oliver and Sick, Beate and R{\"u}gamer, David}
}
@conference {675,
	title = {Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model},
	booktitle = { International Conference on Information Fusion (FUSION)},
	year = {2023},
	pages = {1-8},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Charleston, SC, USA},
	doi = {10.23919/FUSION52260.2023.10224159},
	author = {Patrick Hoher and Johannes Reuter and Daniel Dold and Dennis Griesser and Felix Govaers and Wolfgang Koch}
}
@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}
}
@article {Schuldt2015,
	title = {Design of a dual species atom interferometer for space},
	journal = {Experimental Astronomy},
	volume = {39},
	number = {2},
	year = {2015},
	pages = {167-206},
	doi = {10.1007/s10686-014-9433-y},
	author = {Schuldt, T and Schubert, C and Krutzik, M and Bote, L and Gaaloul, N and Hartwig, J and Ahlers, H and Herr, W and Posso-Trujillo, K and Rudolph, J and Seidel, S and Wendrich, T and Ertmer, W and Herrmann, S and Kubelka-Lange, A and Milke, A and Rievers, B and Rocco, E and Hinton, A and Bongs, K and Oswald, M and M O Franz and Hauth, M and Peters, A and Bawamia, A and Wicht, A and Battelier, B and Bertoldi, A and Bouyer, P and Landragin, A and Massonnet, D and L{\'e}v{\`e}que, T and Wenzlawski, A and Hellmig, O and Windpassinger, P and Sengstock, K and von Klitzing, W and Chaloner, C and Summers, D and Ireland, P and Mateos, I and Sopuerta, C F and Sorrentino, F and Tino, G M and Williams, M and Trenkel, C and Gerardi, D and Chwalla, M and Burkhardt, J and Johann, U and Heske, A and Wille, E and Gehler, M and Cacciapuoti, L and G{\"u}rlebeck, N and Braxmaier, C and Rasel, E}
}
@conference {262,
	title = {Merging multiple 3d face reconstructions},
	booktitle = {Symposium on Information and Communication Systems},
	year = {2014},
	pages = {7-12},
	author = {Leonard Thie{\ss}en and Pascal Laube and M O Franz and Georg Umlauf},
	editor = {Dirk Benyoucef and Christoph Reich}
}
@article {Aguilera2014,
	title = {{STE-QUEST} {\textemdash} {Test} of the universality of free fall using cold atom interferometry},
	journal = {Classical and Quantum Gravity},
	volume = {31},
	number = {11},
	year = {2014},
	pages = {115010},
	author = {D N Aguilera and H Ahlers and B Battelier and A Bawamia and A Bertoldi and R Bondarescu and K Bongs and P Bouyer and C Braxmaier and L Cacciapuoti and C Chaloner and M Chwalla and W Ertmer and M O Franz and N Gaaloul and M Gehler and D Gerardi and L Gesa and N G{\"u}rlebeck and J Hartwig and M Hauth and O Hellmig and W Herr and S Herrmann and A Heske and A Hinton and P Ireland and P Jetzer and U Johann and M Krutzik and A Kubelka and C L{\"a}mmerzahl and A Landragin and I Lloro and D Massonnet and I Mateos and A Milke and M Nofrarias and M Oswald and A Peters and K Posso-Trujillo and E Rasel and E Rocco and A Roura and J Rudolph and W Schleich and C Schubert and T Schuldt and S Seidel and K Sengstock and C F Sopuerta and F Sorrentino and D Summers and G M Tino and C Trenkel and N Uzunoglu and W von Klitzing and R Walser and T Wendrich and A Wenzlawski and P We{\ss}els and A Wicht and E Wille and M Williams and P Windpassinger and N Zahzam}
}
@article {stadelmann2013applied,
	title = {Applied Data Science in Europe: Challenges for Academia in Keeping Up with a Highly Demanded Topic},
	journal = {European Computer Science Summit. Amsterdam, Netherlands},
	year = {2013},
	author = {Stadelmann, T and Stockinger, K and Braschler, M and Cieliebak, M and Baudinot, G and D{\"u}rr, O and Ruckstuhl, A}
}
@conference {198,
	title = {On-line reconstruction of CAD geometry},
	booktitle = {International Conference on 3d Vision},
	year = {2013},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Klaus Denker and Daniel Hagel and Jakob Raible and Georg Umlauf and Bernd Hamann}
}
@conference {192,
	title = {3d hand gesture recognition based on sensor fusion of commodity hardware},
	booktitle = {Mensch und Computer},
	year = {2012},
	publisher = {Oldenbourg Verlag},
	organization = {Oldenbourg Verlag},
	author = {Manuel Caputo and Klaus Denker and Benjamin Dums and Georg Umlauf},
	editor = {H.~Reiterer and O.~Deussen}
}
@article {heyse2005quantifying,
	title = {Quantifying bioactivity on a large scale: quality assurance and analysis of multiparametric ultra-HTS data},
	journal = {JALA: Journal of the Association for Laboratory Automation},
	volume = {10},
	number = {4},
	year = {2005},
	pages = {207{\textendash}212},
	publisher = {SAGE Publications Sage CA: Los Angeles, CA},
	author = {Heyse, Stephan and Brodte, Annette and Bruttger, Oliver and Duerr, Oliver and Freeman, Tobe and Jung, Tom and Lindemann, Michael and Ottl, Johannes and Rinn, Bernd}
}
@conference {Kienzle2004,
	title = {Efficient approximations for support vector machines for object detection},
	booktitle = {{Pattern Recognition, Proc. of the 26th DAGM Symposium}},
	year = {2004},
	pages = {54{\textendash}61},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin},
	author = {Kienzle, W and Bak{\i}r, G H and M O Franz},
	editor = {Rasmussen, C E and B{\"u}lthoff, H H and Giese, M A}
}
@conference {SinEa04,
	title = {Learning depth from stereo},
	booktitle = {{Pattern Recognition, Proc.\ 26th DAGM Symposium}},
	series = {LNCS},
	volume = {3175},
	year = {2004},
	pages = {245~{\textendash}~252},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin},
	author = {F Sinz and J Qui{\~n}onero~Candela and G H Bak{\i}r and C E Rasmussen and M O Franz},
	editor = {C E Rasmussen and H H B{\"u}lthoff and M A Giese and B Sch{\"o}lkopf}
}
@conference {Bakir2004,
	title = {Multivariate Regression via {Stiefel} Manifold Constraints},
	booktitle = {{Pattern Recognition, Proc. of the 26th DAGM Symposium (DAGM 2004)}},
	year = {2004},
	pages = {262-269},
	publisher = {Springer},
	organization = {Springer},
	address = {Heidelberg},
	author = {G H Bak{\i}r and A Gretton and M O Franz and B Sch{\"o}lkopf},
	editor = {Rasmussen, C E and H H B{\"u}lthoff and M A Giese and B Sch{\"o}lkopf}
}
@conference {FraKwoRasSch04,
	title = {Semi-supervised kernel regression using whitened function classes},
	booktitle = {{Pattern Recognition, Proc.\ 26th DAGM Symposium}},
	series = {LNCS},
	volume = {3175},
	year = {2004},
	pages = {18~{\textendash}~26},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin},
	author = {M O Franz and Kwon, Y and Rasmussen, C E and Sch{\"o}lkopf, B},
	editor = {C.~E. Rasmussen and H.~H. B{\"u}lthoff and M.~A. Giese and B. Sch{\"o}lkopf}
}
