Graph Models

Stochastic Steady-state Embedding

Introduced by Dai et al. in Learning Steady-States of Iterative Algorithms over Graphs

Stochastic Steady-state Embedding (SSE) is an algorithm that can learn many steady-state algorithms over graphs. Different from graph neural network family models, SSE is trained stochastically which only requires 1-hop information, but can capture fixed point relationships efficiently and effectively.

Description and Image from: Learning Steady-States of Iterative Algorithms over Graphs

Source: Learning Steady-States of Iterative Algorithms over Graphs

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