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Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods (bibtex)
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods (bibtex)
by L. Della Libera, V. Golkov, Y. Zhu, A. Mielke and D. Cremers
Reference:
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods (L. Della Libera, V. Golkov, Y. Zhu, A. Mielke and D. Cremers), In arXiv preprint arXiv:1910.14594, 2019. 
Bibtex Entry:
@article{Della-Libera-et-al-2019,
 author = {L. Della Libera and V. Golkov and Y. Zhu and A. Mielke and D. Cremers},
 title = {Deep Learning for {2D and 3D} Rotatable Data: An Overview of Methods},
 year = {2019},
 journal = {arXiv preprint arXiv:1910.14594},
 eprint = {1910.14594},
 eprinttype = {arXiv},
 keywords = {deep learning, neural networks, 2D, 3D, rotations, invariance, equivariance},
}
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