Dieses Bild zeigt David Holzmüller

David Holzmüller

M. Sc.

Wissenschaftlicher Mitarbeiter
Institut für Stochastik und Anwendungen
Lehrstuhl für Stochastik

Kontakt

Pfaffenwaldring 57
70569 Stuttgart
Deutschland
Raum: 8.552

Fachgebiet

Forschungsschwerpunkt: Trainingsverhalten von neuronalen Netzen und deren Anwendungsmöglichkeiten im Simulationskontext.

GitHub
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Mein Twitter-Account

Viktor Zaverkin, David Holzmüller, Ingo Steinwart, and Johannes Kästner, Exploring chemical and conformational spaces by batch mode deep active learning, Digital Discovery, 2022. doi.org

David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart, A Framework and Benchmark for Deep Batch Active Learning for Regression, 2022  arxiv.org

Viktor Zaverkin, David Holzmüller, Robin Schuldt, and Johannes Kästner, Predicting properties of periodic systems from cluster data: A case study of liquid water, J. Chem. Phys. 156, 114103, 2022 doi.org

David Holzmüller and Dirk Pflüger, Fast Sparse Grid Operations Using the Unidirectional Principle: A Generalized and Unified Framework, 2021. In: Bungartz, HJ., Garcke, J., Pflüger, D. (eds) Sparse Grids and Applications - Munich 2018. Lecture Notes in Computational Science and Engineering, vol 144. Springer, Cham. doi.org

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 arxiv.org

David Holzmüller, On the Universality of the Double Descent Peak in Ridgeless Regression, 2020 arxiv.org

Daniel F. B. Haeufle, Isabell Wochner, David Holzmüller, Danny Driess, Michael Günther, Syn Schmitt, Muscles Reduce Neuronal Information Load: Quantification of Control Effort in Biological vs. Robotic Pointing and Walking, 2020 https://www.frontiersin.org/articles/10.3389/frobt.2020.00077/full

David Holzmüller, Ingo Steinwart, Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent, 2020 arXiv.org

David Holzmüller, Improved Approximation Schemes for the Restricted Shortest Path Problem, 2017 (https://arxiv.org/abs/1711.00284)

David Holzmüller, Efficient Neighbor-Finding on Space-Filling Curves, 2017 (https://arxiv.org/abs/1710.06384)

Zum Porträt des Monats am Fachbereich, Februar 2020

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