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Neural Information Processing Systems

NeurIPS 2021 : Neural Information Processing Systems (NIPS) (NeurIPS)

Location: Online

Submission deadline: 5/21/2021

Conference dates: 12/6/2021 - 12/6/2021

Research H-index
147

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 7 1421 2370 146
Neuroscience 3 43 54 16

Call for Papers

The Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS 2021) is an interdisciplinary conference that brings together researchers in machine learning, computational neuroscience, statistics, optimization, economics, computer vision, natural language processing, computational biology, and other fields. We invite submissions presenting new and original research on topics including but not limited to the following:

General Machine Learning (e.g., classification, unsupervised learning, transfer learning)
Deep Learning (e.g., architectures, generative models, optimization for deep networks)
Reinforcement Learning (e.g., decision and control, planning, hierarchical RL)
Applications (e.g., speech processing, computational biology, computer vision, NLP)
Probabilistic Methods (e.g., variational inference, causal inference, Gaussian processes)
Optimization (e.g., convex and non-convex optimization)
Neuroscience and Cognitive Science (e.g., neural coding, brain-computer interfaces)
Theory (e.g., control theory, learning theory, algorithmic game theory)
Infrastructure (e.g., datasets, competitions, implementations, libraries)
Social Aspects of Machine Learning (e.g., AI safety, fairness, privacy, interpretability)

Overview

This ranking presents a comprehensive evaluation of scientific conferences within the field of Computer Science. Developed by Research.com, a leading and authoritative website for scientific research evaluation and analytics since 2014, this ranking reflects trusted expertise in the provision of data on scientific contributions across multiple disciplines, including Computer Science.

The position of each conference in this ranking is determined by a unique bibliometric score developed by Research.com. This score incorporates a nuanced analysis based on the estimated h-index as well as the number of leading scientists who have participated in the conference over the previous three years. Such a methodology ensures a balanced and robust assessment of overall conference impact and scientific significance.

The ranking features Impact Score values gathered on 2024-11-27. Its compilation involved the meticulous evaluation of more than 2,742 scientific conferences, which were carefully selected following a rigorous examination of over 148,739 scientific documents published in the last three years by 13,184 eminent and well-respected scientists specializing in Computer Science. This extensive and critical analysis underscores the promise and reliability of the provided ranking.

For an in-depth explanation of the methodology employed to compute the ranking scores, we invite you to refer to our Methodology Page.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing at Neural Information Processing Systems (based on the number of publications) are:

  • Michael I. Jordan (121 papers) published 8 papers at the last edition, 6 more than at the previous edition,
  • Bernhard Schölkopf (89 papers) published 4 papers at the last edition, 2 less than at the previous edition,
  • Yoshua Bengio (79 papers) published 3 papers at the last edition, 6 less than at the previous edition,
  • Francis Bach (66 papers) published 5 papers at the last edition, 6 less than at the previous edition,
  • Geoffrey E. Hinton (63 papers) published 1 paper at the last edition, 2 less than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing at Neural Information Processing Systems (based on the number of publications) are:

  • Massachusetts Institute of Technology (760 papers) published 112 papers at the last edition, 27 more than at the previous edition,
  • Carnegie Mellon University (644 papers) published 91 papers at the last edition, 6 more than at the previous edition,
  • Stanford University (627 papers) published 114 papers at the last edition, 24 more than at the previous edition,
  • Google (621 papers) published 196 papers at the last edition, 60 more than at the previous edition,
  • Microsoft (583 papers) published 110 papers at the last edition, 34 more than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2020 edition, 1.92% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 38.27% were posted by at least one author from the top 10 institutions publishing at the conference. Another 15.49% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.13% of all publications and 27.11% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

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