We invite researchers to submit work in any of the following areas:
- Applications of Bayesian deep learning,
- deep generative models,
- variational inference using neural network recognition models,
- practical approximate inference techniques in Bayesian neural networks,
- applications of Bayesian neural networks,
- information theory in deep learning,
- or any of the topics below.
A submission should take the form of an extended abstract (3 pages long) in PDF format using the NIPS style. Author names do not need to be anonymised and references may extend as far as needed beyond the 3 page upper limit. Submissions may extend beyond the 3 pages upper limit, but reviewers are not expected to read beyond the first 3 pages. If research has previously appeared in a journal, workshop, or conference (including NIPS 2018 conference), the workshop submission should extend that previous work. Parallel submissions (such as to ICLR) are permitted.
Submissions will be accepted as contributed talks or poster presentations. Extended abstracts should be submitted by Friday 2 November 2018; submission page is here. Final versions will be posted on the workshop website (and are archival but do not constitute a proceedings).
- Extended abstract submission deadline: Friday 2 November 2018 (midnight AOE) (submission page is here)
- Acceptance notification: 16 November 2018
- Camera ready submission: 30 November 2018
- Workshop: 7 December 2018
We will do our best to guarantee workshop registration for all accepted workshop submissions — we have multiple workshop tickets reserved for accepted submissions. In addition, several complimentary workshop registrations will be awarded to authors of accepted workshop abstracts. These will be announced by 16 November 2018. Award recipients will be reimbursed by NIPS for their workshop registration. Further workshop endorsements and travel awards to junior researchers will be updated on the workshop website.