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Disambiguation of "Holzmüller, David"

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A Framework and Benchmark for Deep Batch Active Learning for Regression

, , , and . J. Mach. Learn. Res., 24 (164): 1–81 (2023)

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David Holzmüller University of Stuttgart

Dr. Marie Davidova University of Stuttgart

David Pfleger University of Stuttgart

Simulationsgestützte Planung, , , and . Technisches Handbuch Logistik 2: Fördertechnik, Materialfluss, Intralogistik, Springer Berlin Heidelberg, Berlin, Heidelberg, (2020)
Simulationsgestützte Planung, , , and . Technisches Handbuch Logistik 2: Fördertechnik, Materialfluss, Intralogistik, Springer Berlin Heidelberg, Berlin, Heidelberg, (2020)Ermittlung des logistischen und energetischen Flexibilitätspotentials eines Logistikzentrums unter Berücksichtigung von Elektromobilität, , , , , and . Wissenschaftliche Gesellschaft für Technische Logistik e. V. (WGTL), (2020)VR-basierte Planung logistischer Systeme: Entwicklung von Einsatzszenarien und Inbetriebnahme einer Versuchsumgebung, and . Tagungsband zum 13. Fachkolloquium der Wissenschaftlichen Gesellschaft für Technische Logistik e. V. (WGTL), 13, (2017)

David Inkermann

David Briesenick University of Stuttgart

 

Other publications of authors with the same name

Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression. Software, (2021)Related to: David Holzmüller. On the Universality of the Double Descent Peak in Ridgeless Regression. International Conference on Learning Representations, 2021. arXiv: 2010.01851.A Framework and Benchmark for Deep Batch Active Learning for Regression, , , and . J. Mach. Learn. Res., 24 (164): 1–81 (2023)Convergence rates for non-log-concave sampling and log-partition estimation, and . arXiv:2303.03237, (2023)Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments, , , and . Software, (2021)Related to: V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner, “Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments,” J. Chem. Theory Comput. 17, 6658–6670 (2021). doi: 10.1021/acs.jctc.1c00527.Transfer learning for chemically accurate interatomic neural network potentials, , , and . Physical chemistry, chemical physics, 25 (7): 5383-5396 (2023)Muscles reduce neuronal information load: quantification of control effort in biological vs robotic pointing and walking, , , , , and . Frontiers in Robotics and AI, (2020)Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent, and . (2020)A Framework and Benchmark for Deep Batch Active Learning for Regression, , , and . Journal of Machine Learning Research, 24 (164): 1--81 (2023)Transfer learning for chemically accurate interatomic neural network potentials, , , and . Phys. Chem. Chem. Phys., 25 (7): 5383-5396 (2023)Fast Sparse Grid Operations Using the Unidirectional Principle: A Generalized and Unified Framework, and . Sparse Grids and Applications - Munich 2018, page 69--100. Cham, Springer International Publishing, (2021)