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François Charton

4 papers hereh-index 6745 citations9 works total

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

author position
  • first author1
  • middle author1
  • last author2

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

fields
  • cs.LG1
  • cs.SC1
  • cs.SE1
  • cs.SI1
same name
  • François Charton — 8 papers, h 3
  • François Charton — 8 papers, h 6
  • François Charton — 7 papers, h 5
  • François Charton — 2 papers
  • François Charton — 1 paper
  • François Charton — 1 paper

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

activity
20192023
most citedDeep Learning for Symbolic Mathematics

47 citations · 61 across the 4 of their papers we have counts for

collaborators

4 papers

cs.SI2023★ 3 cited

A mimetic approach to social influence on Instagram

Hubert Etienne, François Charton

We combine philosophical theories with quantitative analyses of online data to propose a sophisticated approach to social media influencers. Identifying influencers as communicatio…

cs.LG2021★ 1 cited

A deep language model to predict metabolic network equilibria

François Charton, Amaury Hayat, Sean T. McQuade +2

We show that deep learning models, and especially architectures like the Transformer, originally intended for natural language, can be trained on randomly generated datasets to pre…

cs.SE2021★ 10 cited

Leveraging Automated Unit Tests for Unsupervised Code Translation

Baptiste Roziere, Jie M. Zhang, Francois Charton +3

With little to no parallel data available for programming languages, unsupervised methods are well-suited to source code translation. However, the majority of unsupervised machine…

cs.SC2019★ 47 cited

Deep Learning for Symbolic Mathematics

Guillaume Lample, François Charton

Neural networks have a reputation for being better at solving statistical or approximate problems than at performing calculations or working with symbolic data. In this paper, we s…

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