Path Independent Equilibrium Models Can Better Exploit Test-Time Computation. (arXiv:2211.09961v1 [cs.LG])

Designing networks capable of attaining better performance with an increased
inference budget is important to facilitate generalization to harder problem
instances. Recent efforts have shown promising results in this direction by
making use of depth-wise recurrent networks. We show that a broad class of
architectures named equilibrium models display strong upwards generalization,
and find that stronger performance on harder examples (which require more
iterations of inference to get correct) strongly correlates with the path
independence of the system -- its …

arxiv computation equilibrium independent path test