2024
Submissions
We are inviting researchers to present a poster during our poster session. Please submit your work here:
Investigators interested in having their abstracts considered for presentation should submit their abstracts no later than August 31, 2024.
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
Submissions
We are inviting researchers to present a poster during our poster session. Please submit your work here:
Investigators interested in having their abstracts considered for presentation should submit their abstracts no later than August 31, 2024.
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
- Statistics
- Physics
- Computer science
- Neuroscience
- Mathematics
- Psychology
- Engineering
- Statistics
- Physics
- Computer science
- Neuroscience
- Mathematics
- Psychology
- Engineering
Topics may address any area of deep learning research such as:
Topics may address any area of deep learning research such as:
- Expressivity
- Generalization
- Optimization
- Representations
- Computation
- Network architectures
- Recurrent networks
- Expressivity
- Generalization
- Optimization
- Representations
- Computation
- Network architectures
- Recurrent networks
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.
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.
submissions close August 31, 2024, AoE
submissions close August 31, 2024, AoE
Latex template available here(1 page + additonal page for references)
Latex template available here
(1 page + additonal page for references)
double-blind review
double-blind review