See my CV for further detail on my learning and professional experience.

Research interests

My current research interests are centered on analogy and the challenges of representation learning, from the axis of deep learning.

Analogical reasoning (AR) and analogical proportions, which are the topic of my Ph.D., are full of potential to capture a key mechanism of human reasoning capability. AR allows to reason and transfer knowledge within and across domains, in a similar manner as case-based reasoning. A key advantage of AR is the ease of interpretation: the mechanism itself is intuitive, and allows for examples and counterexamples to be found.

Contact & social

You can contact me by mail at esteban.marquer@loria.fr. You can also find me on:

• LinkedIn;
• Research Gate;
• Google Scholar;
• PapersWithCode;
• DeepAI;
• HAL;
• arXiv;
• GitHub and GitLab.

Teaching

You can find various ressources I use for teaching here. You can see the list of my teaching experience in my CV.

Key publications

The following bublications are those I consider the most representative of my work. You can see a list of all my publications here.

• S. Alsaidi, A. Decker, P. Lay, E. Marquer, P.-A. Murena, M. Couceiro.
  A Neural Approach for Detecting Morphological Analogies.
  The 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct 2021, Porto/Online, Portugal.
  Paper (on HAL); Poster (on HAL).
• E. Marquer, A. Kulkarni, M. Couceiro.
  Embedding Formal Contexts Using Unordered Composition.
  FCA4AI - 8th International Workshop “What can FCA do for Artificial Intelligence?” (colocated wit ECAI2020), Aug 2020, Santiago de Compostela, Spain.
  Paper.