[1] D. Auge, J. Hille, E. Mueller, and A. Knoll, "A Survey of Encoding Techniques for Signal Processing in Spiking Neural Networks," Neural Processing Letters, vol. 53, no. 6, pp. 4693–4710, Dec. 2021. doi: 10.1007/s11063-021-10562-2.
[2] E. Mueller, V. Studenyak, D. Auge, and A. Knoll, "Spiking Transformer Networks: A Rate Coded Approach for Processing Sequential Data," in Proc. 2021 7th International Conference on Systems and Informatics (ICSAI), 2021, pp. 1–5. doi: 10.1109/ICSAI53574.2021.9664146.
[3] E. Mueller, D. Auge, S. Klimaschka, and A. Knoll, "Neural oscillations for energy-efficient hardware implementation of sparsely activated deep spiking neural networks," in Proc. AAAI Conf. Artif. Intell. (AAAI), 2022.
[4] E. Mueller, D. Auge, and A. Knoll, "Exploiting inhomogeneities of subthreshold transistors as populations of spiking neurons," in Proc. Int. Conf. Natural Comput., Fuzzy Syst. Knowl. Discovery (ICNC-FSKD), Lecture Notes on Data Engineering and Communications Technologies, vol. 153. Cham, Switzerland: Springer, 2022, pp. 483–492, doi: 10.1007/978-3-031-20738-9_55.
[5] E. Mueller, J. Hansjakob, D. Auge, and A. Knoll, "Minimizing Inference Time: Optimization Methods for Converted Deep Spiking Neural Networks," in Proc. 2021 International Joint Conference on Neural Networks (IJCNN), 2021, pp. 1–8. doi: 10.1109/IJCNN52387.2021.9533874.
2023: Doctor of Philosophy in Computer Science, Technical University of Munich, Germany
2017: Master of Science in Product Development, Materials and Production, Technical University of Hamburg, Germany
2014: Bachelor of Science in Mechanical Engineering, Technical University of Hamburg, Germany
