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M. Gaimann, und M. Klopotek. Dataset, (2025)Related to: Gaimann, M. U., & Klopotek, M. (2025). Robustly optimal dynamics for active matter reservoir computing. arXiv: 2505.05420.
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S. Kolin, M. Marquardt, G. Fläschner, S. Naumann, und K. Pluhackova. Dataset, (2025)Related to: Molecular determinants of solvent nanoseparation by nanoporous carbon materials Sofia Kolin, Moritz G. Marquardt, Gotthold Fläschner, Stefan Naumann, and Kristyna Pluhackova.
S. Tovey, K. Nikolaou, S. Krippendorf, C. Holm, und M. Spannowsky. Software, (2025)Related to: Tovey, Samuel James, Sven Krippendorf, Michael Spannowsky, Konstantin Nikolaou, and Christian Holm. “Collective Variables of Neural Networks: Empirical Time Evolution and Scaling Laws.” Machine Learning: Science and Technology, 2025. doi: 10.1088/2632-2153/adee76.
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M. Gaimann, und M. Klopotek. Dataset, (2025)Related to: Gaimann, M. U., & Klopotek, M. (2025). Robustly optimal dynamics for active matter reservoir computing. arXiv: 2505.05420.
T. Fellner, S. Tovey, C. Holm, und M. Spannowsky. Software, (2025)Related to: Tovey, Samuel, et al. "Generating Reservoir State Descriptions with Random Matrices." arXiv preprint (2024). doi: 10.48550/arXiv.2404.07278.
K. Pluhackova, C. Pfaendner, B. Unger, und V. Korn. Software, (2025)Related to: Pfaendner, C., Korn, V., Gogoi, P., Unger, B., Pluhackova, K. (2025). ART-SM: Boosting Fragment-Based Backmapping by Machine Learning. Journal of Chemical Theory and Computation. doi: 10.1021/acs.jctc.5c00189.
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