mlsanityData to 7 Oct 2026

AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework

arXiv 2308.03321 ↗First posted 7 Aug 2023cs.LG cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

The success of deep learning is inseparable from normalization layers. Researchers have proposed various normalization functions, and each of them has both advantages and disadvantages. In response, efforts have been made to design a unified normalization function that combines all normalization procedures and mitigates their weaknesses. We also proposed a new normalization function called Adaptive Fusion Normalization. Through experiments, we demonstrate AFN outperforms the previous normalization techniques in domain generalization and image classification tasks.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 20 of its 28 references that are in the map. First posted on arXiv 7 Aug 2023.

Builds on

20 of 28 references.

References · 20

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  3. 2016Layer Normalizationcited by 5,579
  4. 2016Wide Residual Networkscited by 3,057
  5. 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,857
  6. 2014Unsupervised Domain Adaptation by Backpropagationcited by 1,906
  7. 2016Instance Normalization: The Missing Ingredient for Fast Stylizationcited by 1,187
  8. 2017Deeper, Broader and Artier Domain Generalizationcited by 983
  9. 2018Generalizing to Unseen Domains via Adversarial Data Augmentationcited by 451
  10. 2020Self-Challenging Improves Cross-Domain Generalizationcited by 426
  11. 2020Learning to Learn Single Domain Generalizationcited by 295
  12. 2020Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustnesscited by 121
8 more
  1. 2023Rethinking Model Ensemble in Transfer-based Adversarial Attackscited by 88
  2. 2021Adversarially Adaptive Normalization for Single Domain Generalizationcited by 85
  3. 2018Batch-Instance Normalization for Adaptively Style-Invariant Neural Networkscited by 77
  4. 2022T-SEA: Transfer-based Self-Ensemble Attack on Object Detectioncited by 59
  5. 2018Differentiable Learning-to-Normalize via Switchable Normalizationcited by 33
  6. 2022Learning to Generalize across Domains on Single Test Samplescited by 24
  7. 2022Bootstrap Generalization Ability from Loss Landscape Perspectivecited by 16
  8. 2022Understanding and Improving Group Normalizationcited by 2

Built on by

Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024Rethinking Centered Kernel Alignment in Knowledge Distillationcited by 17
  2. 2024Quantile Activation: Correcting a Failure Mode of ML Modelscited by 1