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:
April 30, 2023May 15, 2023 - Reviews released:
May 30, 2023June 2, 2023 - Final papers submission: June 10, 2023
- Conference dates: June 19-21, 2023
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 Lecture Notes in Computer Science (https://resource-cms.springernature.com/springer-cms/rest/v1/content/19238648/data/v6)
Papes should be sent using the following link
CaDis 