DeepMath 2025: Call for Abstracts
We are pleased to announce DeepMath 2025: the 7th installment of the Conference for the Mathematical Theory of Deep Learning (www.deepmath-conference.com). This year DeepMath will be held at the University of Michigan in Ann Arbor Michigan. We have a stellar lineup of invited speakers including:
We are inviting researchers to present a poster during our poster session. Please submit your work no later than August 31, 2025 on OpenReview using the following link:
https://openreview.net/group?id=deepmath-conference.com/DeepMath/2025/Conference
DeepMath is a highly interdisciplinary conference focused on understanding fundamental theory driving the success of Deep Learning. A principal goal of this conference is to bring together theoreticians working on deep learning from various disciplines and perspectives. We, therefore, encourage submissions from researchers from diverse disciplines including but not limited to
Topics may address any area of deep learning research such as:
To complement the many conferences with applications and theory the focus for DeepMath will be exclusively on the theoretical and mechanistic understanding of the underlying properties of neural networks.
Abstracts will not be made public (i.e., no official proceedings), and will be doubly-blind reviewed and selected for quality. All poster submissions should be properly anonymized in order to allow for blind refereeing. Submissions should be no more than 1 page although a second page may be used for references. Authors should submit a pdf file prepared using the Latex style file available here and should adopt all formatting, subject headings, font sizes, etc. defined therein. Submissions that fail to meet the format requirements will not be reviewed. The first author listed on the abstract is considered to be the presenting author. Each presenting author may submit only one abstract.