2023: Workshop on Causal Discovery CaDis 2023

This volume contains the proceedings of the 1st Workshop on Causal Discovery (CaDis 2023). The workshop was held at the Na- tional Institute of Astrophysics, Optics and Electronics (INAOE) in Tonatzintla, Puebla, Mexico, June 19–21, 2023.

Causal models have many advantages, including the ability to reason about the effects of interventions, as well as the results of different scenarios or counterfactuals. The traditional approach for building causal models is by conducting experiments, however these are often infeasible, unethical or too expensive. Recently there has been a lot of interest in the scientific community to learn causal models from observational data, but this is a great challenge, as just from observations is not possible, in general, to define a unique causal model.

The objective of this workshop was to present recent advances in causal discovery, including different approaches that consider observational and/or interventional data, and also building models with the help of human experts. It is also of interest the combina- tion of causal discovery with other areas of machine learning, such as reinforcement learning and deep learning; as well as real-world applications.