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Disambiguation of "Mueller, Christian L."

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Inverse Dirichlet weighting enables reliable training of physics informed neural networks

, , , and . Machine learning: science and technology, (Feb 15, 2022)Funding Information: This work was supported by the German Research Foundation (DFG) – EXC-2068, Cluster of Excellence ‘Physics of Life’, and by the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, funded by the Federal Ministry of Education and Research (BMBF). The present work was also partly funded by the Center for Advanced Systems Understanding (CASUS), which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament. Publisher Copyright: © 2022 The Author(s). Published by IOP Publishing Ltd..
DOI: 10.1088/2632-2153/ac3712

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Yuhao Liu

NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs, , , and . 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), page 85-92. (2023)
NetPU-M: a Generic Reconfigurable Neural Network Accelerator Architecture for MLPs, , , and . 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), page 85-92. (2023)High-Flexibility Designs of Quantized Runtime Reconfigurable Multi-Precision Multipliers, , , and . IEEE Embedded Systems Letters, 15 (4): 194-197 (2023)BitSys: Bitwise Systolic Array Architecture for Multi-precision Quantized Hardware Accelerators, , and . 2024 IEEE 32nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), page 220-220. (2024)

Martin Lorenz

Visual Sampling Behavior Does not Explain Risk Perception: A Data-Driven xAI Investigation, , , , and . Proceedings of the 17th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, New York, NY, USA, Association for Computing Machinery, (2025)
 

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Inverse Dirichlet weighting enables reliable training of physics informed neural networks, , , and . Machine learning: science and technology, (Feb 15, 2022)Funding Information: This work was supported by the German Research Foundation (DFG) – EXC-2068, Cluster of Excellence ‘Physics of Life’, and by the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, funded by the Federal Ministry of Education and Research (BMBF). The present work was also partly funded by the Center for Advanced Systems Understanding (CASUS), which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament. Publisher Copyright: © 2022 The Author(s). Published by IOP Publishing Ltd..