Geometric Deep Learning book
ML resource: Published at ICLR 2021, Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges is a free 150-page proto-book by Bronstein et al. (2021) that “attempts to distill ‘all you need to build the architectures that are all you need.’” They express popular architectures like CNNs, GNNs, Transformers and LSTMs all using a common geometric blueprint. Co-author Petar Veličković on Twitter: “Hence we believe that our work can be a useful way to navigate the increasingly challenging landscape of deep learning architectures.” Direct PDF link (large).