Harder, Hans, and Sebastian Peitz. Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.

Althoff, Simon. Predicting the Bond Quality of Heavy Copper Wire Bonds Using a Friction Model Approach. Shaker, 2023.

Qudus, Umair, et al. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.”10.1007/978-3-031-47240-4_25__The Semantic Web – ISWC 2023, edited by Terry R. Payne et al., vol. 14265, Springer, Cham, 2023, pp. 465–483, doi:10.1007/978-3-031-47240-4_25.

Kersting, Joschka, et al. “Towards Comparable Ratings: Exploring Bias in German Physician Reviews.”10.1016/j.datak.2023.102235__Data &; Knowledge Engineering, vol. 148, 102235, Elsevier, 2023, doi:10.1016/j.datak.2023.102235.

Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.”https://doi.org/10.36001/phme.2021.v6i1.2843 __Proceedings of the European Conference of the PHM Society 2021, edited by Phuchttps://doi.org/10.36001/phme.2021.v6i1.2843 __Do et al., vol. 6, no. 1, 2021, doi:https://doi.org/10.36001/phme.2021.v6i1.2843 .

Schroder, Dominik, et al. “Far-Field Prediction Combining Simulations with near-Field Measurements for EMI Assessment of PCBs.”10.1049/pbcs072e_ch14__Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis, 1st ed.,10.1049/pbcs072e_ch14__The Institution of Engineering and Technology (IET), 2020, pp. 315-346 (32), doi:10.1049/pbcs072e_ch14.

Aimiyekagbon, Osarenren Kennedy, et al. “Evaluation of Time Series Forecasting Approaches for the Reliable Crack Length Prediction of Riveted Aluminium Plates given Insufficient Data.” PHM Society European Conference, vol. 5, no. 1, 2020.

Bender, Amelie, et al. “Remaining Useful Lifetime Prediction Based on Adaptive Failure Thresholds.” Proceedings of the 29th European Safety and Reliability Conference (ESREL2019), edited by Michael Beer and Enrico Zio, no. 29, 2019, pp. 1262–69.

Sievers, Sönke, et al. Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence. 2017, doi:10.2139/ssrn.2237757.

Klobucnik, Jan, et al. “Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence.” SSRN Electronic Journal, 2017.

Sprock, Christian, and Walter Sextro. “Time-Efficient Dynamic Analysis of Structures Exhibiting Nonlinear Peak Bending.”10.1109/I2MTC.2014.6860760__Instrumentation and Measurement Technology Conference (MTC) Proceedings, 2014 IEEE International, 2014, pp. 320–24, doi:10.1109/I2MTC.2014.6860760.

Nallaperuma, Samadhi, et al. “A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem.”10.1145/2460239.2460253__Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII, Association for Computing Machinery, 2013, pp. 147–160, doi:10.1145/2460239.2460253.

Sievers, Sönke, and Christopher Frederik Mokwa. The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. 2012, doi:10.2139/ssrn.2100501.

Hunstig, Matthias, et al. “An Efficient Simulation Technique for High-Frequency Piezoelectric Inertia Motors.”10.1109/ULTSYM.2012.0068__Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 277–80, doi:10.1109/ULTSYM.2012.0068.

Mokwa, Christopher Frederik, and Sönke Sievers. “The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments.”10.2139/ssrn.2100501__SSRN Electronic Journal, 2012, doi:10.2139/ssrn.2100501.