Publications

Bomze I, Rinaldi F, Zeffiro D. Fast cluster detection in networks by first-order optimization. SIAM Journal on Mathematics of Data Science. 2022 Mar 4;4(1):285-305. Epub 2021 Mar 29. doi: 10.1137/21M1408658

Bauer L, Hirsch F, Jones C, Hollander M, Grohs P, Anand A et al. Quantification of Kuramoto Coupling Between Intrinsic Brain Networks Applied to fMRI Data in Major Depressive Disorder. Frontiers in Computational Neuroscience. 2022 Mar 3;16:729556. doi: 10.3389/fncom.2022.729556

Schneckenreiter G, Herrmann L, Reisenhofer R, Popper N, Grohs P. Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data. medRxiv. 2022 Mar 1. doi: https://doi.org/10.1101/2022.02.21.22271241

Kinast A , Dörner KF, Rinderle-Ma S. Combing metaheuristics and process mining: Improving cobot placement in a combined cobot assignment and job shop scheduling problem. In Procedia Computer Science. Vol. 200. Elsevier. 2022. p. 1836-1845 doi: 10.1016/j.procs.2022.01.384

Huggins JE, Krusienski D, Vansteensel MJ, Valeriani D, Thelen A, Stavisky S et al. Workshops of the eighth international brain–computer interface meeting: BCIs: the next frontier. Brain-Computer Interfaces. 2022 Feb 8;9(2):69-101. doi: 10.1080/2326263X.2021.2009654

Kutyniok G, Petersen PC, Raslan M, Schneider R. A theoretical analysis of deep neural networks and parametric PDEs. Constructive Approximation. 2022 Feb;55(1):73-125. Epub 2021 Jun 2. doi: 10.1007/s00365-021-09551-4

Elbrächter D, Grohs P, Jentzen A, Schwab C. DNN Expression Rate Analysis of High-dimensional PDEs: Application to Option Pricing. Constructive Approximation. 2022 Feb;55(1):3-71. Epub 2021 May 6. doi: 10.1007/s00365-021-09541-6

Braune R, Benda F, Dörner KF , Hartl R. A Genetic Programming Learning Approach to Generate Dispatching Rules for Flexible Shop Scheduling Problems. International Journal of Production Economics. 2022 Jan;243:108342. doi: 10.1016/j.ijpe.2021.108342

Markham A, Das R, Grosse-Wentrup M. A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations. Proceedings of Machine Learning Research (PMLR). 2022;177:542-558.

Leiber C, Mautz D, Plant C , Böhm C. Automatic Parameter Selection for Non-Redundant Clustering. In Banerjee A, Zhou Z-H, Papalexakis EE, Riondato M, editors, Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022, Alexandria, VA, USA, April 28-30, 2022. SIAM. 2022. p. 226-234 doi: 10.1137/1.9781611977172.26

Durani W, Mautz D, Plant C , Böhm C. DBHD: Density-based clustering for highly varying density. In IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022. IEEE. 2022. p. 921-926

Velaj Y , Dolezal D , Ambros R , Plant C , Motschnig R. Designing a Data Science Course for Non-Computer Science Students: Practical Considerations and Findings. In 2022 IEEE Frontiers in Education Conference, FIE 2022. Piscataway, NJ: IEEE. 2022. p. 1-9 doi: 10.1109/FIE56618.2022.9962455

Wu H, Tan S, Li W, Garrard M, Obeng A, Dimmery D et al.. Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies. 2022. Paper presented at 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Washington DC, District of Columbia, United States.

Kozobolis S, Ioannidis A, Pasch H , Heinisch B, Nuč-Blažič A, Orthaber S et al. Forschungsbericht - ReTrans Working with Interpreters in Refugee Transit Zones: Capacity building and awareness-raising for higher education contexts: Work Package 1 Final Report. 2022.

Gerard L , Scherbela M, Marquetand P, Grohs P. Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?. 2022. Paper presented at Thirty-sixth Conference on Neural Information Processing Systems, New Orleans, United States.

Balazia M, Hlavácková-Schindler K, Sojka P, Plant C. Interpretable Gait Recognition by Granger Causality. In 26th International Conference on Pattern Recognition, ICPR 2022, Montreal, QC, Canada, August 21-25, 2022. Piscataway, NJ: IEEE. 2022. p. 1069-1075 doi: 10.48550/arXiv.2206.06714, 10.1109/ICPR56361.2022.9956624

Arbour D, Dimmery D, Mai T, Rao A. Online Balanced Experimental Design. 2022. Paper presented at International Conference on Machine Learning (ICML), Baltimore, United States.

Leiber C, Bauer LGM, Neumayr M, Plant C , Böhm C. The DipEncoder: Enforcing Multimodality in Autoencoders. In Zhang A, Rangwala H, editors, KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM. 2022. p. 846-856 doi: 10.1145/3534678.3539407

Böhm A, Sedlmayer M , Csetnek ER , Bot RI. Two steps at a time -- taking GAN training in stride with Tseng's method. SIAM Journal on Mathematics of Data Science. 2022;4(2):750-771.

Plant C, Hubig NC, Shao J, Ottley A, Gou L, Möller T et al. Visualization in Data Science VDS @ KDD 2022. In Zhang A, Rangwala H, editors, KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM. 2022. p. 4894-4895 doi: 10.1145/3534678.3542903