GABE: Groupwise Affine Basis Encoding

Introduce GABE (Groupwise Affine Basis Encoding) - a decomposition method that represents neural network weights as an addressable memory system. For any group of similar layers, we extract three interpretable components: a shared mean weight (long-term memory), a low-rank basis of variations (address space), and per-layer coefficients (pointers).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-05
DOI
https://doi.org/10.5281/zenodo.18488810
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
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article

GABE: Groupwise Affine Basis Encoding

Dmitry F. Feklin
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

GABE: Groupwise Affine Basis Encoding

Dmitry F. Feklin
article en

Abstract

Introduce GABE (Groupwise Affine Basis Encoding) - a decomposition method that represents neural network weights as an addressable memory system. For any group of similar layers, we extract three interpretable components: a shared mean weight (long-term memory), a low-rank basis of variations (address space), and per-layer coefficients (pointers).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 68%
Adversarial Robustness in Machine Learning
DOIOpen Access PDFOpenAlex
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GABE: Groupwise Affine Basis Encoding — Dmitry F. Feklin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS