( en | de | ru )

 

Disambiguation of "Garcke, Jochen"

Author of the publication

copydeleteadd this publication to your clipboard
Statusreport: Chancen mit Big Data -- Best Practice

, , , , , , , , , , , , , , , , , , , , and . VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik, (2016)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Jochen Garcke

Harald Garcke

Peter Garcke

Harald Garcke

Harald Garcke

 

Other publications of authors with the same name

Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems, , , , , , , , , and 4 other author(s). (2019)cite arxiv:1903.12394Comment: Accepted at IEEE Transactions on Knowledge and Data Engineering: https://ieeexplore.ieee.org/document/9429985.Data Analytics for Simulation Repositories in Industry., and . GI-Jahrestagung, volume P-232 of LNI, page 161-167. GI, (2014)Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes., and . WACV, page 2344-2353. IEEE, (2022)Statusreport: Chancen mit Big Data -- Best Practice, , , , , , , , , and 11 other author(s). VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik, (2016)Explainable machine learning for scientific insights and discoveries, , , and . Ieee Access, (2020)Decision Support by Interpretable Machine Learning in Acoustic Emission Based Cutting Tool Wear Prediction., , , , , , , and . IEEM, page 629-633. IEEE, (2021)How Does Knowledge Injection Help in Informed Machine Learning?, , and . IJCNN, page 1-8. IEEE, (2023)The pole balancing problem from the viewpoint of system flexibility., , and . GECCO Companion, page 427-430. ACM, (2022)Transfer Learning Using Spectral Convolutional Autoencoders on Semi-Regular Surface Meshes., , and . LoG, volume 198 of Proceedings of Machine Learning Research, page 18. PMLR, (2022)Canonical convolutional neural networks., , , and . IJCNN, page 1-8. IEEE, (2022)