CAWS 2023: Causal Analysis Workshop Series 2023 University of Minnesota Minneapolis, MN, United States, August 14-15, 2023 |
Conference website | https://cawsnetwork.com/caws-2023-call-for-papers/ |
Submission link | https://easychair.org/conferences/?conf=caws2023 |
Abstract registration deadline | June 11, 2023 |
Submission deadline | June 11, 2023 |
CAWS (https://cawsnetwork.com/caws-2023-call-for-papers/) promotes the development and application of causal discovery and related methods, identifies challenges in causal inference and causal discovery that require the development of new causally informed algorithms and statistical procedures, guides the field of causal analysis towards establishing best practices, and provides a venue for causal analysis researchers to share and communicate their findings.
Submission Guidelines
- Full Paper: maximum 12 pages.
- Invited to give virtual talk
- Can choose to include revised paper in special issue of Proceedings of Machine Learning Research.
- Short paper: maximum 3 pages
- Invited to give virtual talk
- Mini: 1 page
- Invited to give brief virtual talk / tech demo
- Intended primarily for promoting tools that will help the community, including freely available data repositories and software
Authors of all accepted papers will be invited to participate in a Round Table Discussion at the end of the event, a summary of which may be published in the proceedings.
All submissions must use the PMLR paper style. Papers do not need to be anonymized. References and appendices may extend beyond the page limit.
List of Topics
Some examples of appropriate research topics are:
- Development/improvement of automated causal modeling methods
- Application or evaluation of automated causal modeling methods
- Causal effect estimation by data driven causal structure discovery
- Predictive modeling applications guided by causal structure discovery
- Causal discovery leveraging combined information in prior knowledge, using heterogeneous data
- Automated identification of optimal interventions from discovered causal models
Invited Speakers
- Our 2023 Keynote Speaker is Glenn Saxe!
Publication
CAWS 2023 proceedings will be published in PMLR.
Venue
The conference will be held virtually.
Contact
All questions about submissions should be emailed to rawls017@umn.edu, erichk@umn.edu, sisima@umn.edu, or andr1017@umn.edu