98 citations · 622 across the 36 of their papers we have counts for
3 papers · 1 filter
Controlling Neural Level Sets
Matan Atzmon, Niv Haim, Lior Yariv +3
The level sets of neural networks represent fundamental properties such as decision boundaries of classifiers and are used to model non-linear manifold data such as curves and surf…
Provably Powerful Graph Networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky +1
Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressive power of graph neural networks (GNN). It was shown that the popular message passing G…
On the Universality of Invariant Networks
Haggai Maron, Ethan Fetaya, Nimrod Segol +1
Constraining linear layers in neural networks to respect symmetry transformations from a group is a common design principle for invariant networks that has found many applicati…