DAGSHOP — A Workshop on directed acyclic graphs

Directed Acyclic Graphs (DAGs) appear in many contexts in network science, from citation networks and pedigrees to temporal-network event graphs and representations of discretized spacetime in quantum gravity. They are also widely used in machine learning, e.g., in Bayesian networks. The particular strength of DAGs comes from their capability to represent temporal and causal structures: e.g., the time-respecting paths of temporal networks and the causal structure of spacetime with future and past lightcones can be readily mapped onto DAGs. However, at the time being, research on DAGs is scattered across different subfields of network science, mathematics, and computer science. The purpose of DAGshop is to unite these various lines of research and gather network scientists interested in learning about the properties and use of directed acyclic graphs.

The scope of the satellite symposium is to explore and showcase the potential of DAG-based approaches in network science. In this spirit, the satellite aims to create the opportunity for cross-pollination between different disciplines and to build an interdisciplinary community around this topic.

Topics covered by DAGShop include:

• Causality in networks
• Temporal event graphs
• Temporal-network embeddings
• Directed acyclic graphs in machine learning
• Citation networks
• Pedigrees and family trees
• DAGs in spacetime physics and quantum gravity

SUBMIT A CONTRIBUTION

If you want to present your research in DAGSHOP’25, please submit a 1-page PDF abstract to dagshop25@gmail.com before February 17, 2025!