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Weisfeiler-Leman Hierarchy

The Weisfeiler–Leman (WL) hierarchy is a family of color-refinement procedures that iteratively color vertices (or k-tuples of vertices) to capture graph structure for isomorphism testing.

#weisfeiler-leman#color refinement#graph isomorphism+12
📚TheoryAdvanced

E(n) Equivariant Neural Networks

E(n)-equivariant neural networks are models whose outputs transform predictably when inputs are rotated, translated, or reflected in n-dimensional Euclidean space.

#e(n)-equivariance
Intermediate
Advanced
Group:
Geometric Deep Learning
#euclidean group
#so(n) and o(n)
+12
📚TheoryAdvanced

Gauge Equivariant Networks

Gauge equivariant networks are neural networks that respect local symmetries (gauges) on manifolds, such as how vectors rotate when you change the local reference frame on a surface.

#gauge equivariant networks#geometric deep learning#manifold learning+12