Typical NIPS papers often (but not always) include a mix of algorithmic, theoretical, and experimental results, in varying proportions. Submissions that satisfy the previous requirements will be judged on the basis of their technical quality, novelty, potential impact, and clarity. Submissions that have fatal flaws revealed by the reviewers, including (without limitation) incorrect proofs or flawed or insufficient wet-lab, hardware, or software experiments, may be rejected on that basis, without taking into consideration other criteria. The reviews and meta-reviews of accepted papers will be made publicly available.Įvaluation Criteria: Submissions that violate the NIPS style guide or page limits, are not within the scope of NIPS (see technical areas below), or have already been published elsewhere (see dual submission policy below) may be rejected by the area chairs without further review. It is the responsibility of the authors to ensure the proper anonymization of their paper. Reviewing: Reviewing will be double-blind: the reviewers will not know the identities of the authors. Looking at any supplementary material is up to the discretion of the reviewers.
Supplementary Material: Authors can submit up to 100 MB of material, containing proofs, additional details, data, or source code.
Camera-ready papers will be due in advance of the conference however, authors will be allowed to make minor changes, such as fixing typos and adding additional references, for a certain period of time after the conference.įrequently Asked Questions can be found here.
Additional pages containing only cited references are allowed. Papers are limited to eight pages, including figures and tables, in the NIPS style. Submissions are solicited for the Thirty-First Annual Conference on Neural Information Processing Systems (NIPS 2017), an interdisciplinary conference that brings together researchers in all aspects of neural and statistical information processing and computation, and their applications.Īll submissions will be made in PDF format.
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