Lucas Zimmer
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Nas-bench-301 and the case for surrogate benchmarks for neural architecture search
J Siems, L Zimmer, A Zela, J Lukasik, M Keuper, F Hutter
arXiv preprint arXiv:2008.09777, 2020
Auto-Pytorch: Multi-fidelity metalearning for efficient and robust AutoDL
L Zimmer, M Lindauer, F Hutter
IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (9), 3079-3090, 2021
Surrogate NAS benchmarks: Going beyond the limited search spaces of tabular NAS benchmarks
A Zela, JN Siems, L Zimmer, J Lukasik, M Keuper, F Hutter
Tenth International Conference on Learning Representations, 1-36, 2022
Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
I Ezhov, K Scibilia, K Franitza, F Steinbauer, S Shit, L Zimmer, J Lipkova, ...
arXiv preprint arXiv:2111.04090, 2021
Calibration of intensity spectra from fluorescent nuclear track detectors in clinical ion beams
A Verkhovtsev, L Zimmer, S Greilich
Radiation Measurements 121, 37-41, 2019
A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling
I Ezhov, L Zimmer, B Menze
arXiv. org, 2022
Casting the inverse problem as a database query. The case of personalized tumor growth modeling
I Ezhov, M Rosier, L Zimmer, F Kofler, S Shit, J Paetzold, K Scibilia, ...
arXiv preprint arXiv:2205.04550, 2022
Method, device and computer program for predicting a suitable configuration of a machine learning system for a training data set
A Zela, F Hutter, J Siems, L Zimmer
US Patent App. 16/950,570, 2021
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