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researcher

Victor Quétu

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CV1
  • cs.LG1
ORCID 0009-0004-2795-3749
same name
  • Victor Quétu — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSparse Double Descent in Vision Transformers: real or phantom threat?

2 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024★ 2 cited

Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization Layers

Zhu Liao, Nour Hezbri, Victor Quétu +2

Today, deep neural networks are widely used since they can handle a variety of complex tasks. Their generality makes them very powerful tools in modern technology. However, deep ne…

cs.AI2023

The Quest of Finding the Antidote to Sparse Double Descent

Victor Quétu, Marta Milovanović

In energy-efficient schemes, finding the optimal size of deep learning models is very important and has a broad impact. Meanwhile, recent studies have reported an unexpected phenom…

cs.CV2023★ 2 cited

Sparse Double Descent in Vision Transformers: real or phantom threat?

Victor Quétu, Marta Milovanovic, Enzo Tartaglione

Vision transformers (ViT) have been of broad interest in recent theoretical and empirical works. They are state-of-the-art thanks to their attention-based approach, which boosts th…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.