Call for Papers

The call for papers is now closed.

We invite submissions contributing novel research at the intersection of geometric deep learning, computational neuroscience, geometric statistics, and topological data analysis, which incorporate symmetry, geometry, or topology into the design of artificial neural networks, the analysis of neural data, or theories of neural computation.

The following themes are particularly relevant:

  • Group-invariance and equivariance

  • Manifold learning

  • Disentangled representations

  • Estimation on manifolds and Lie groups

We hope to see both theoretical contributions and applied results in domains including vision, motor control, and navigation, as well as the use of diverse mathematical objects such as quotient spaces, fiber bundles, Lie groups, Riemannian manifolds, graphs, and group representations. We are also interested in submissions contributing benchmark datasets or software. This list is intended to provide guidance, but it is far from exhaustive. If you are unsure whether your work is within scope of this workshop, please reach out to the organizers.

There are two tracks for submission to NeurReps. Submissions to both tracks will be featured during the workshop's poster session, and a subset of all submissions will be selected for spotlight talks.

  1. Proceedings Track

NeurReps Proceedings papers may be up to 9 pages long, excluding references and appendices. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR) Volume on Symmetry and Geometry in Neural Representations. This track is appropriate for self-contained research papers with a high degree of development.

2. Extended Abstract Track

Extended abstracts may be up to 4 pages long, excluding references and appendices. This track creates space for contributions such as early-stage results, insightful negative findings, opinion pieces, or novel datasets. Extended abstracts will not be included in the PMLR volume, but authors may post to arXiv under the NeurReps index.

Dual Submission Policy

Papers in the Proceedings Track will be archivally published in PMLR. Thus, submissions containing content that has been published or submitted elsewhere must include at least 30% new, unpublished/unsubmitted material. Likewise, to publish a NeurReps paper in another venue down the line, authors must add at least 30% new material. There are no restrictions on Extended Abstract submissions.

Review Process

Reviews are double-blind and conducted through OpenReview. All submissions will receive a minimum of three reviews.

Dates and Deadlines

Submission: September 25, 2022 11:59 PM Pacific Time (PT)
Author Notification:
October 20, 2022 11:59 PM Pacific Time (PT)

Submission Instructions

All submissions must use the NeurReps 2022 LaTeX style files: [Overleaf template], [.zip].

Authors should select the proceedings or extended abstract format in the pmlr-sample.tex file.

All submissions should be submitted to OpenReview using the link below.

Please reach out to with any questions.