Randomly initialized networks trained solely via peer-to-peer self-distillation learn useful representations that outperform random baselines on downstream tasks.
Densely connected convolutional networks,
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Randomly Initialized Networks Can Learn from Peer-to-Peer Consensus
Randomly initialized networks trained solely via peer-to-peer self-distillation learn useful representations that outperform random baselines on downstream tasks.