Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers

Lin, B. (2021). Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers. Entropy, 24(1), 59. https://doi.org/10.3390/e24010059

Authors:

Baihan Lin

Affiliated Authors:

Baihan Lin

Columbia Affiliation:

Vagelos College of Physicians and Surgeons
- Department of Neuroscience
- Department of Systems Biology

Subjects:

Advances in Transfer Learning and Domain Adaptation (OpenAlex Topic)

Explainable Artificial Intelligence (OpenAlex Topic)

Adversarial Robustness in Deep Learning Models (OpenAlex Topic)

Author Keywords:

neuronal coding

biologically plausible models

minimum description length

deep neural networks

normalization methods

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Publication Type:

Article

Unique ID:

10.3390/e24010059

PMID:

35052085

DOI:

10.3390/e24010059

Journal:

Entropy

Publication Date:

2022-01-22

Data Source:

PubMed

Source Link:

View PubMed Record

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View Web of Science Record

View OpenAlex Record

Record Created:

Wednesday, February 19, 2025 - 11:47