Causal learning

  • Artificial Intelligence & data intelligence,
  • PostDoc
  • Paris – Saclay
  • Level 8
  • 2024-07-01
  • POLI Jean-Philippe (DRT/DIN)

As part of a project that concerns the creation of innovative materials, we wish to strengthen our platform in its ability to learn from little experimental data. In particular, we wish to work firstly on the extraction of causal links between manufacturing parameters and properties. Causality extraction is a subject of great importance in AI today and we wish to adapt existing approaches to experimental data and their particularities in order to select the variables of interest. Secondly, we will focus on these causal links and their characterization (causal inference) using an approach based on fuzzy rules, that is to say we will create fuzzy rules adapted to their representation.

doctorat informatique, IA


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