Methods › General › Normalization

Normalization

38 methods 32,100 papers tagged archive 2025-07-28

The archive attaches this collection's text per method and the copies differ: 2 distinct texts across 38 of the 38 methods here. All are shown, most-carried first (a tie goes to the text carrying Papers with Code's collection boilerplate, then to the longer text); no vote is taken between them.

Text 1, carried by 36 of 38 methods:

Normalization layers in deep learning are used to make optimization easier by smoothing the loss surface of the network. Below you will find a continuously updating list of normalization methods.

Text 2, carried by 2 of 38 methods:

Regularization strategies are designed to reduce the test error of a machine learning algorithm, possibly at the expense of training error. Many different forms of regularization exist in the field of deep learning. Below you can find a constantly updating list of regularization strategies.

Methods

All 38 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.


Layer Normalization	–	24,980
Batch Normalization	–	6,287
Instance Normalization	–	572
Adaptive Instance Normalization	–	429
Local Response Normalization	–	421
Spectral Normalization	–	220
Weight Demodulation	–	182
Conditional Batch Normalization	–	145
Weight Normalization	–	88
Activation Normalization	–	61
Group Normalization	–	55
SPADE Spatially-Adaptive Normalization	–	38
SRN Stable Rank Normalization	–	17
Gradient Normalization	–	15
RMSNorm Root Mean Square Layer Normalization	–	14
MPN Matrix-power Normalization	–	13
LayerScale	–	12
Weight Standardization	–	12
Switchable Normalization	–	9
Local Contrast Normalization	2009	8
ReZero	–	7
SyncBN Synchronized Batch Normalization	–	5
Decorrelated Batch Normalization	–	4
Mixture Normalization	–	4
Attentive Normalization	–	3
Conditional Instance Normalization	–	3
Online Normalization	–	3
Cosine Normalization	–	2
Filter Response Normalization	–	2
InPlace-ABN In-Place Activated Batch Normalization	–	2
Mode Normalization	–	2
BatchChannel Normalization	–	1
CInC Flow Characterizable Invertible 3x3 Convolution	–	1
EvoNorms	–	1
Instance-Level Meta Normalization	–	1
SaBN Sandwich Batch Normalization	–	1
Sparse Switchable Normalization	–	1
Virtual Batch Normalization	–	1