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architectureIntroduced by ResNet · 2015

Residual connection

Add a layer's input to its output so very deep networks stay trainable.

Drafted by AI · not yet reviewed

How this idea evolved

Each step is the idea’s introducing paper. The line between steps is the citation link between those papers.

  1. 2014
    VGGVery deep 3×3 ConvNets

    Stack many small 3×3 convolutions; depth alone drives accuracy.

    Cites · not yet reviewedcited 11× · §Deep Residual Learning
    “Our plain baselines (Fig. 3, middle) are mainly inspired by the philosophy of VGG nets Simonyan2015 (Fig. 3, left).”
    From ResNet · §Deep Residual Learning
  2. 2015
    ResNetResidual connection

    Add a layer's input to its output so very deep networks stay trainable.

Papers using this