Scale-Equivariant Deep Learning for 3D Data (bibtex)
by T Wimmer, V Golkov, HN Dang, M Zaiss, A Maier and D Cremers
Reference:
Scale-Equivariant Deep Learning for 3D Data (T Wimmer, V Golkov, HN Dang, M Zaiss, A Maier and D Cremers), In arXiv preprint, 2023. 
Bibtex Entry:
@article{Wimmer2023,
 title = {Scale-Equivariant Deep Learning for 3D Data},
 author = {T Wimmer and V Golkov and HN Dang and M Zaiss and A Maier and D Cremers},
 year = {2023},
 journal = {arXiv preprint},
 eprint = {2304.05864},
 eprinttype = {arXiv},
 primaryclass = {cs.CV},
 keywords = {deep learning, equivariant deep learning, scale-equivariance, magnetic resonance imaging, image segmentation, medical imaging},
}
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Scale-Equivariant Deep Learning for 3D Data (bibtex)
Scale-Equivariant Deep Learning for 3D Data (bibtex)
by T Wimmer, V Golkov, HN Dang, M Zaiss, A Maier and D Cremers
Reference:
Scale-Equivariant Deep Learning for 3D Data (T Wimmer, V Golkov, HN Dang, M Zaiss, A Maier and D Cremers), In arXiv preprint, 2023. 
Bibtex Entry:
@article{Wimmer2023,
 title = {Scale-Equivariant Deep Learning for 3D Data},
 author = {T Wimmer and V Golkov and HN Dang and M Zaiss and A Maier and D Cremers},
 year = {2023},
 journal = {arXiv preprint},
 eprint = {2304.05864},
 eprinttype = {arXiv},
 primaryclass = {cs.CV},
 keywords = {deep learning, equivariant deep learning, scale-equivariance, magnetic resonance imaging, image segmentation, medical imaging},
}
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members:golkov

Dr. Vladimir Golkov

Postdoctoral ResearcherTechnical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17777
Fax: +49-89-289-17757
Office: 02.09.061
Mail: vladimir.golkov@tum.de

Students who did projects under my supervision went on to become PhD students of Prof. Cremers, Prof. Navab, Prof. Rost, Prof. Nießner, Prof. Haddadin, Prof. Precup, Prof. Razansky, Prof. Ntziachristos (with Prof. van der Smagt), Prof. Griffin & Prof. Kleinberg, Prof. Van Gool, Prof. Schindler, Prof. Liò, Prof. Theis, and others.

Quick links: C++, Matlab (without password), Python, NumPy, best coding practices, software craftsmanship, student projects, mathematical image processing (free access through TUM), proximal algorithms, biology, literature network 1 2, research and scientific writing 1 2 3, thesis guide, soft skills manual for students, TUM Career Guide for International Students, TUM Career Manual, PhD scholarships 1 2 3 4 etc., conferences, Ten Simple Rules series

Grant support: Deutsche Telekom Foundation