from September 24th to September 29th 2023
Organizers : MIAI, CNRS, AISSAI
Partner : SFdS
This school takes place in a thematic quarter that underlines the interactions between Statistical, Probability Theory, Causal Inference theory, and theoretical computer science methods for causal inference. It will enable researchers, students, and practitioners to explore a rich and cross-disciplinary topic. This thematic quarter will explore topics related to, but not limited to:
- Causal discovery
- Causal learning and control problems
- Theoretical foundation of causal inference
- Causal inference and active learning
- Causal learning in low data regime
- Reinforcement learning
- Causal machine learning
- Causal generative models
- Benchmark for causal discovery and causal reasoning
This school particularly focuses on practical aspects, by introducing the main packages available nowadays for causal discovery and causal reasoning.
See the program
Link for payment