[CFP] NeurIPS 2024 Workshop on Foundation Models for Science (FM4Science)

[Wuyang Chen]

Working on foundation models for scientific problems? Consider submitting your paper to the 1st Workshop on Foundation Models for Science (FM4Science) at NeurIPS 2024 in Vancouver!

Submission details: https://fm-science.github.io/cfp.html
OpenReview submission portal: https://openreview.net/group?id=NeurIPS.cc/2024/Workshop/FM4Science

Tentative important dates (AoE time):

• Abstract Submission Deadline: August 27, 2024
• Paper Submission Deadline: August 30, 2024
• Review Bidding Period: August 30 - September 2, 2024
• Reviewer Deadline: September 27, 2024
• Acceptance/Rejection Notification Date: September 30, 2024
• Workshop Date: December 14 or 15, 2024

Topics: include but are not limited to:

• How to achieve better scaling laws for foundation models in scientific problems by designing datasets, network architectures, and training algorithms?
• How to design data augmentation and multi-modal self-supervised pretraining for scientific problems?
• How to design efficient fine-tuning with scientific awareness?
• How to quantify and reduce the uncertainty of scientific foundation models?
• How to improve the out-of-distribution generalization of scientific foundation models?
• How to make foundation models compatible with and enable the integration of classic scientific tools (simulators, solvers, etc.)?
• How toientific foundation models benefit from the reasoning and in-context learning of LLMs?
• How to better combine symbolic learning and data-driven learning?
• How to use foundation models to facilitate visualizations in scientific problems?
• How to accelerate scientific discovery and the collection/assimilation of scientific data with foundation models?
• How to diagnose failure cases or modes where scientific foundation models do not perform well?
• How to align scientific foundation models with scientific facts without hallucination?

Scientific Domains. We invite paper submissions from various scientific domains, including but not limited to: Astrophysics and Space Science, Biomedicine (e.g., proteins, biosequences, virtual screening), Computational Science (e.g., PDEs, forecasting), Earth Science, Materials Science (e.g., batteries, chemical synthesis), Quantum Mechanics (e.g., nuclear fusion), Small Molecules. Applications-driven submissions focusing on AI-for-Science and Scientific Machine Learning (SciML) are also highly encouraged.

Awards. Among exceptional research papers with high review scores, we will select one best paper award and two runner-ups.

For other information about our workshop, please visit: https://fm-science.github.io/index.html

If you have any questions about paper submission and the workshop, please send email to: foundationm...@gmail.com

We look forward to your contributions!

Sincerely,

Wuyang

--
Wuyang Chen, Ph.D.
Assistant Professor of Computing Science
Simon Fraser University, Burnaby, BC, Canada
Pronouns: he/him/his
https://delta-lab-ai.github.io/
https://www.sfu.ca/computing/people/faculty/chen--wuyang.html