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 is 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 combination of causal discovery with other areas of machine learning, such as reinforcement learning and deep learning; as well as real-world applications.

The fourth edition of CaDis will take place at INAOE in Tonantzintla, Puebla, México, which will be held in a hybrid format, in person and virtual.

Submission Guidelines

We invite contributions relevant to any aspect of causal discovery, including theoretical and practical aspects, and applications. The submissions can be in any of the following topics, but not limited to:

• Causal discovery from observational data
• Causal discovery from interventions
• Hybrid causal discovery
• Building causal models from human expert knowledge
• Causal discovery from time series
• Reinforcement learning and causal discovery
• Deep learning and causal discovery
• Benchmarks for causal discovery
• Applications to real-world problems

Important dates:

• Paper submission deadline: August 10
• Reviews release: September 15
• Final papers submission: September 20
• Conference date: November 30 – December 1

Submissions:

We accept two types of submissions: (i) normal papers that present a relevant contribution (limited to 12 pages), (ii) extended abstracts for preliminary work or proof of concept research (limited to 4 pages). Both should be formatted according to Springer’s Communications in Computer and Information Science (https://link.springer.com/series/558/information-for-authors-and-editors)

Papers should be sent using the following link.

The presentation format will be hybrid, either in-person or virtual, according to the authors’ preferences.

Publication

The Workshop’s Proceedings will be published by Springer in the Communications in Computer and Information Science (CCIS) series.

Contact

All questions about submissions should be emailed to cadis@inaoep.mx