Geometric deep learning: Grids, groups, graphs, geodesics, and gauges
Michael M Bronstein, Joan Bruna, Taco Cohen, Petar Veličković
Paper
From BibTeX import
arXiv preprint arXiv:2104.13478, 2021
Notes
Cited in riva2026random to flag gauge equivariance as a design principle in geometric deep learning, reinforcing that the differential-geometric vocabulary we deploy is shared across architectures on manifolds.
References
No references yet.