Workshop on Causal Discovery (CaDis 2024) November 12th, Montevideo, Uruaguay

https://cadisworkshop.com.mx

The CaDis workshop will be held at the IBERAMIA'2024 conference.

The objective of this workshop is to present recent advances in causaldiscovery, including different approaches that consider observationaland/or interventional data, and also building models with the help ofhuman experts. It is also of interest the combination of causaldiscovery with other areas of machine learning, such as reinforcementlearning and deep learning; as well as real worl applications. 

We invite contributons 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

Importan dates

• Paper submission deadline: September 15.
• Reviews release: October 15.
• Final paper submission: October 31.
• Conference date: November 12.

Authors of best papers will be invited to submit extended versiosn to "Causal Graphical Models and Their Applications", a special issue of "Entropy" (https://www.mdpi.com/journal/entropy/special_issues/BSPSAJX3SL)

Invited Speakers

• Prof. David Danks

Professor of Data Science, Philosophy, & Policy at University ofCalifornia, San Diego

• Prof. Kung Shang

Professor and the acting department chair of machine learning at Mohamedbin Zayed University of Artificial Intelligence (MBZUAI), and associateprofessor at Carnegie Mellon University.