Call for Papers

Important dates

(All deadlines are 23:59 Oslo Time)

Submission: September 01, 2025
Review period: September 17 to October 08, 2025
Emergency reviews: October 08 to 14, 2025
Rebuttal for authors: October 15 to 22, 2025
Post-rebuttal review (reviewers to authors): October 22 - 27, 2025
Final decisions (reviewer & AC discussion): October 27 - 31, 2025
Author notification: November 05, 2025

Call for Papers

The 2026 edition of the Northern Lights Deep Learning Conference (NLDL) will take place on 6-8 January 2025 in Tromsø, Norway, organized by Visual Intelligence and the UiT Machine Learning Group.

We look forward to gathering the deep learning community again in the cool arctic air for a physical conference.

In addition, the NLDL winter school, which is a part of the NORA research school http://nora.ai, starts on Jan 5, ends on Jan 9, and incorporates events during the main conference days. The winter school includes scientific topics, an industry event, women in AI event, and transferable skills. More information is coming soon at http://www.nldl.org/winter-school.

We invite submissions presenting new and original research on all aspects of Deep Learning. The topics include but are not limited to the following:

General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, supervised, semi- and self-supervised learning, time series analysis, etc.)
General Deep Learning (architectures, generative models, deep reinforcement learning, etc.)
Optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.)
Probabilistic methods (Bayesian methods, variational inference, graphical models, etc.)
Social and economic aspects of Machine Learning (accountability, causality, fairness, privacy, robustness, interpretability, etc.)
Applications (vision, language, signals, speech and audio, etc.)
Deep Learning for Sciences (biology and medicine, environment and ecology, physics, etc.)

As always, we are happy to have top international speakers, see the keynotes here.

How to submit a contribution

We invite participants to submit in PDF format a 5 to 8 pages full paper (included in proceedings) in the area of Deep Learning. References and appendix can go beyond the page limit.

All submissions will undergo double-blind peer review. It will be up to the authors to ensure the proper anonymization of their paper. Do not include any names or affiliations. Refer to your own past work in the third-person, or if needed insert a blank reference. Accepted contributions will be accepted as contributing talks or poster presentations.

Submissions must be PDF files which follow the template we provide. This template is a LaTeX template. Therefore, authors have to use LaTeX to write their paper. We do not provide any Word template and we discourage authors from using Word for their submission. You can download the latest packaged template here or follow the instructions in the repository to clone the template. Detailed style guidelines can be found within the main.tex, its compiled version for the full papers, or in the compiled versions here.

Reference instructions

References need to include a DOI (if it exists)
When citing arXiv papers, the authors need to check if the paper has been published. If there is a published version of the paper, it should be cited instead of the arXiv version.

Additional information

All authors must have registered an account in Open Review (no exceptions).
Authors cannot be added to the papers once the review process has started (no exceptions).
We allow authors to upload a preprint of the submitted papers to arXiv.
For the camera ready version of accepted papers, we allow the authors to add a 6th page to their paper in order to address requests from the reviewers
At least one author must register for the conference and present their work in person.
Authors must read the guidelines here.

Follow the following link to submit your submission in Open Review:

Submission Portal

Proceedings

There will be a peer-review process for the NLDL submissions and these contributions are to be considered as 'full' publications. The proceedings will be published through Proceedings of Machine Learning Research. The proceedings have been accepted as a Level 1 publication in the Norwegian system.

Copyright for accepted papers

Papers aimed for proceedings should follow general dual submission policies and submissions that are identical or substantially similar to papers that are in submission to, have been accepted to, or have been published in other archival conferences, journals, workshops, etc. will be rejected. Authors should clearly state any overlapping published or submitted work at the time of submission. Authors should ensure that they are not violating any other venue dual submission policies. Papers in proceedings will be assigned the CCBY 4.0 license, and must sign a publication license agreement with PMLR.

Questions & Problems

For questions about the submission process, check the Author FAQ. For problems with the submission side, please contact the program chairs: nldl.conf@gmail.com.

Contacting PCs: the PCs will be fully dedicated to ensuring the proper allocation of papers to suitable ACs and reviewers and to overseeing the review process. PCs will strictly adhere to the following policies:

- Late submissions will not be accepted under any circumstances.
- Submissions of papers, or updates to papers, via email will not be accepted.
- Requests to modify lists of authors will not be considered, regardless of the justification provided.
- Detailed elucidation of the policies will not be provided.
- Questions already answered in the FAQ will not be answered by contacting the PCs.

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