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by rasbt on 2019-11-30 (UTC).

"Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks" -"[a] combination of a normalization and an activation function, that can be used as a drop-in replacement for other normalizations and activations" https://t.co/2hNIOyLSPB pic.twitter.com/ZYnljedsmB

— Sebastian Raschka (@rasbt) November 30, 2019
research
by slashML on 2019-12-01 (UTC).

Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks https://t.co/NIrYLYsmUj

— /MachineLearning (@slashML) December 1, 2019
research
by ajmooch on 2021-01-22 (UTC).

Normalizer-Free ResNets: Our ICLR2021 paper w/ @sohamde_& @SamuelMLSmith

We show how to train deep ResNets w/o *any* normalization to ImageNet test accuracies competitive with ResNets, and EfficientNets at a range of FLOP budgets, while training faster.https://t.co/2WMhCkaxJh pic.twitter.com/nwF7lT25BK

— Andy Brock (@ajmooch) January 22, 2021
researchcv
by ak92501 on 2021-02-12 (UTC).

High-Performance Large-Scale Image Recognition Without Normalization
pdf: https://t.co/THe2NfRI1K
abs: https://t.co/Z68FevANZP
github: https://t.co/Gvw5s5HZIh pic.twitter.com/PGrLhn5oyl

— AK (@ak92501) February 12, 2021
researchw_code

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