Internship offers – year 2022-2023
- Toward efficient then explainable models: Choquetization of a Neural Net.
- The goal of the internship is to educate a trained neural net into being interpretable: i) forcing the decision to be a readable aggregate (Hierarchical Choquet Integral) of latent nodes; ii) formulating binary problems to give a name to each latent node, with the expert in the loop.
- contact: sebag@lri.fr, cohen@lri.fr
- Details here
- Stability-based causal discovery: an adversarial approach
- An important desired property for causal discovery is identifiability. The internship makes a step toward identifiability and focuses on stability, that is, the property of finding the same model from i) true data D; ii) data D’ generated after the model learned from D.
- contact: alessandro.leite@inria.fr, sebag@lri.fr
- Details here
