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Artificial Intelligence and Statistics 2024

  • 2 May 2024
  • (CEST)
  • 4 May 2024
  • (CEST)
  • Valencia, Spain

Call for Papers

They invite submissions to the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), and welcome paper submissions on artificial intelligence, machine learning, statistics, and related areas.

AISTATS is an interdisciplinary gathering of researchers at the intersection of computer science, artificial intelligence, machine learning, statistics, and related areas. Since its inception in 1985, the primary goal of AISTATS has been to broaden research in these fields by promoting the exchange of ideas among them. The conference is committed to diversity in all its forms, and encourages submissions from authors of underrepresented groups and geographies in ML/AI.

Key dates

  • Abstract deadline: 6 October 2023 (Anywhere on Earth)
  • Paper submission deadline: 13 October 2023 (Anywhere on Earth)
  • Appendix submission deadline: 20 October 2023
  • Reviews released: 27 November 2023
  • Author rebuttals due: 5 December 2023 (Anywhere on Earth)
  • Paper decision notifications: 19 January 2024
  • Conference dates: May 2 - May 4, 2024

Paper Submission (Proceedings Track)

The proceedings track is the standard AISTATS paper submission track. Papers will be selected via a rigorous double-blind peer-review process. All accepted papers will be presented at the Conference as contributed talks or as posters and will be published in the Proceedings.

Solicited topics include, but are not limited to:

  • Machine learning methods and algorithms (classification, regression, unsupervised and semi-supervised learning, clustering, logic programming, …)
  • Probabilistic methods (Bayesian methods, approximate inference, density estimation, tractable probabilistic models, probabilistic programming, …)
  • Theory of machine learning and statistics (optimization, computational learning theory, decision theory, online leaning and bandits, game theory, frequentist statistics, information theory, …)
  • Deep learning (theory, architectures, generative models, optimization for neural networks, …)
  • Reinforcement learning (theory of RL, offline/online RL, deep RL, multi-agent RL, …)
  • Ethical and trustworthy machine learning (causality, fairness, interpretability, privacy, robustness, safety, …)
  • Applications of machine learning and statistics (including natural language, signal processing, computer vision, physical sciences, social sciences, sustainability and climate, healthcare, …)

Formatting and Supplementary Material

Submissions are limited to 8 pages excluding references using the LaTeX style file we provide below (the page limit will be 9 for camera-ready submissions). The number of pages containing only citations and the reproducibility checklist is not limited. You can also submit a single file of additional supplementary material which may be either a pdf file (such as proof details) or a zip file for other formats/more files (such as code or videos). Note that reviewers are under no obligation to examine the supplementary material. If you have only one supplementary pdf file, please upload it as is; otherwise gather everything to the single zip file.

Submissions are accepted at

Formatting information (including LaTeX style files) is available in the AISTATS2024PaperPack. We do not support submission in preparation systems other than LaTeX. Please do not modify the layout given by the style file. If you have questions about the style file or its usage, please contact the publications chair or the program chairs via

For more information about submission or registration click here.

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