Call for Papers
Our workshop is nonarchival, the accepted papers will be posted on our website. Our workshop calls for high-quality and cutting-edge paper submissions in the following two tracks:
(A) Original Research Track
This track calls for 4-8 page paper (with unlimited references and appendices) of high-quality contributions from AI applications to all fields of scientific discovery, ranging from physics, biology, chemistry, earth science, environmental science, mechanical science, aerospace science, management science, agricultural science, material science, nuclear science etc. Appendix is optional, but reviewers are not required to read.
Example topics include (but not limited to):
- Learning from acoustics
- Learning physical dynamics from data
- Speeding up physical simulators, samplers and solvers
- Molecular modeling and de novo generation
- Modeling biological systems, genomics, protein, RNA
- Accelerating cosmological simulations
- Improving crop yields through precision agriculture
- Optimizing aerospace product design and development
- Benchmarking related or new tasks (i.e. datasets, sota models, etc.)
- Building tools/infrastructures/platforms for scientific discovery
- Study of science of science/scientific methods
(B) Attention Track
This track solicits 4-8 page paper (with unlimited references and appendices) that highlights a perspective of a subject in the field of AI for Science. We especially welcome contributions that discuss the gaps between AI and Science.
Example topics include (but not limited to):
- Unrealistic ML methodological assumptions
- Overlooked scientific questions
- Opportunities on the intersections of multiple disciplines
- Future research directions/hypothesis of an application area
- Responsible use and development of AI for science
(C) Highlight Track
This track solicits 4-8 page paper (with unlimited references and appendices) that is comprehensive survey/benchmark on a specific topic under AI4Science, e.g., ML for Molecules, comparing with the original track, this track is more focused on the are more interested in summarising the published works.
Example topics include (but not limited to):
- ML for Molecule design
- ML for symbolic regression
- ML for combinatorial optimization
- ML for simulation
Submission Instructions
Abstract is due on Sep 25th AoE, and submisssion is due on Oct 2nd AoE. All submissions are managed through OpenReview.
The review process is double-blind so the submission should be anonymized. We welcome submissions that are (1) originally unpublished, (2) recently published, or (3) work-in-progress. Please use AI for Science template Latex files. Note that for attention track submissions, authors are required to set ‘\usepackage[attention]{neurips_2021}’ to indicate. Accepted papers would be archived on the workshop website. Contributed talks and best paper awards would be given based on review scores and chairs discussion.