HOPSE encodes higher-order topological data by applying graph positional and structural encoders to Hasse graph decompositions, matching or exceeding message-passing models on benchmarks with up to 7x faster training.
E (n) equivariant topological neural networks
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations
HOPSE encodes higher-order topological data by applying graph positional and structural encoders to Hasse graph decompositions, matching or exceeding message-passing models on benchmarks with up to 7x faster training.