3D Deep Learning for Biological Function Prediction from Physical Fields (bibtex)
by V. Golkov, M. J. Skwark, A. Mirchev, G. Dikov, A. R. Geanes, J. Mendenhall, J. Meiler and D. Cremers
Reference:
3D Deep Learning for Biological Function Prediction from Physical Fields (V. Golkov, M. J. Skwark, A. Mirchev, G. Dikov, A. R. Geanes, J. Mendenhall, J. Meiler and D. Cremers), In International Conference on 3D Vision (3DV), 2020. 
Bibtex Entry:
@inproceedings{Golkov-et-al-arxiv2017-function3d,
 author = {V. Golkov and M. J. Skwark and A. Mirchev and G. Dikov and A. R. Geanes and J. Mendenhall and J. Meiler and D. Cremers},
 title = {{3D} Deep Learning for Biological Function Prediction from Physical Fields},
 booktitle = {International Conference on 3D Vision (3DV)},
 year = {2020},
 journal = {arXiv preprint arXiv:1704.04039},
 eprint = {1704.04039},
 eprinttype = {arXiv},
 keywords = {computational structural biology, deep learning, convolutional networks, protein function, QSAR, deep learning, biology},
}
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3D Deep Learning for Biological Function Prediction from Physical Fields (bibtex)
3D Deep Learning for Biological Function Prediction from Physical Fields (bibtex)
by V. Golkov, M. J. Skwark, A. Mirchev, G. Dikov, A. R. Geanes, J. Mendenhall, J. Meiler and D. Cremers
Reference:
3D Deep Learning for Biological Function Prediction from Physical Fields (V. Golkov, M. J. Skwark, A. Mirchev, G. Dikov, A. R. Geanes, J. Mendenhall, J. Meiler and D. Cremers), In International Conference on 3D Vision (3DV), 2020. 
Bibtex Entry:
@inproceedings{Golkov-et-al-arxiv2017-function3d,
 author = {V. Golkov and M. J. Skwark and A. Mirchev and G. Dikov and A. R. Geanes and J. Mendenhall and J. Meiler and D. Cremers},
 title = {{3D} Deep Learning for Biological Function Prediction from Physical Fields},
 booktitle = {International Conference on 3D Vision (3DV)},
 year = {2020},
 journal = {arXiv preprint arXiv:1704.04039},
 eprint = {1704.04039},
 eprinttype = {arXiv},
 keywords = {computational structural biology, deep learning, convolutional networks, protein function, QSAR, deep learning, biology},
}
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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