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researcher

Nicolas Michel

4 papers here

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

author position
  • first author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • math.HO1
ORCID 0000-0002-6265-6748
same name
  • Nicolas Michel — 1 paper, h 3

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 citedContrastive Learning for Online Semi-Supervised General Continual Learning

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

collaborators

4 papers

cs.LG2023★ 1 cited

Domain-Aware Augmentations for Unsupervised Online General Continual Learning

Nicolas Michel, Romain Negrel, Giovanni Chierchia +1

Continual Learning has been challenging, especially when dealing with unsupervised scenarios such as Unsupervised Online General Continual Learning (UOGCL), where the learning agen…

cs.LG2023★ 1 cited

New metrics for analyzing continual learners

Nicolas Michel, Giovanni Chierchia, Romain Negrel +2

Deep neural networks have shown remarkable performance when trained on independent and identically distributed data from a fixed set of classes. However, in real-world scenarios, i…

math.HO2023

Retour d'exp{é}rience : Int{é}grer des applications transverses (Physique et Chimie) de l'enseignement de l'Alg{è}bre

Mickael Bosco, Nicolas Michel

As a Physicist and a Chemist , we have had the opportunity to teach Algebra in our engineering school in Aix-en-Provence. The article deals with the interactions made between Physi…

cs.LG2022★ 1 cited

Contrastive Learning for Online Semi-Supervised General Continual Learning

Nicolas Michel, Romain Negrel, Giovanni Chierchia +1

We study Online Continual Learning with missing labels and propose SemiCon, a new contrastive loss designed for partly labeled data. We demonstrate its efficiency by devising a mem…

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