Physical Networks Become What They Learn.
Sign Up to like & getrecommendations! Published in 2024 at "Physical review letters"
DOI: 10.1103/physrevlett.134.147402
Abstract: Physical networks can develop tuned responses, or functions, by design, by evolution, or by learning via local rules. In all of these cases, tunable degrees of freedom characterizing internal interactions are modified to lower a… read more here.
Keywords: cost; networks become; become learn; physical networks ... See more keywords
Norm-Preservation: Why Residual Networks Can Become Extremely Deep?
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2020.2990339
Abstract: Augmenting neural networks with skip connections, as introduced in the so-called ResNet architecture, surprised the community by enabling the training of networks of more than 1,000 layers with significant performance gains. This paper deciphers ResNet… read more here.
Keywords: preservation; norm preservation; residual networks; networks become ... See more keywords