The theory of belief functions, also referred to as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modelling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the transferable belief model and the theory of hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion and risk analysis.
The biennal BELIEF conferences, sponsored by the Belief Functions and Applications Society, are dedicated to the confrontation of ideas, the reporting of recent achievements and the presentation of the wide range of applications of this theory. The first edition of this conference series was held in Brest, France, in 2010. Later editions were held in Compiègne, France in 2012, Oxford, UK in 2014, Prague, Czech Republic in 2016, and again in Compiègne, France in 2018. The previous edition was delayed by the global pandemic and took place in 2021 in Beijing, China. The Seventh International Conference on Belief Functions (BELIEF 2022) will be located in Paris, France, and it will take place on October 26-28, 2022.
Proceedings of BELIEF 2022 will be published by Springer-Verlag in a volume of the Lecture Notes in Artificial Intelligence (LNCS/LNAI) series and indexed by: ISI Web of Science; EI Engineering Index; ACM Digital Library; dblp; Google Scholar; IO-Port; MathSciNet; Scopus; Zentralblatt MATH. Previous BELIEF proceedings can be found on SpringerLink.
Thanks to the continued support of the International Journal of Approximate Reasoning, the best papers presented at the conference will be distinguished by the IJAR Best Paper Award. The prize will consist of a certificate and 1000 euros, which will be split between the winners.
Authors should submit their papers through Easychair - conference BELIEF 2022 following the Springer LNCS/LNAI series template, also available in Overleaf.
The expected length of papers is no longer than 10 pages, references included, that should present original contributions with significant results. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each accepted paper, acting on behalf of all of the authors of that paper, will have to complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made.
Original contributions are solicited on theoretical aspects including, but not limited to
as well as on applications to various areas including, but not limited to
Authors of selected papers from the BELIEF 2022 conference will be invited to submit extended versions of their papers for possible inclusion in a special issue of the International Journal of Approximate Reasoning.
The BELIEF 2022 Organizing Committee invites proposals for Special Sessions on specific or emerging topics in image processing, such as specific applications as well as the links between machine learning and uncertain reasoning, including topics such as quantification of prediction uncertainty, learning data fusion rules, links with symbolic AI. Proposals will be evaluated based on topic timeliness and expected impact. The papers in each accepted Special Session will undergo a review process similar to that of the regular papers submitted to BELIEF 2022. Special Session proposals must contain the following information:
Researcher Rémi Bardenet, CRIStAL, CNRS and Lille University, France.
Title: Topics in Monte Carlo computation and Bayesian learning
Abstract: to be announced.
Professor Stéphane Canu, INSA Rouen, France.
Title: Robustness of neural networks and adversarial attacks
Abstract: to be announced.
Assoc. Professor Philippe Xu, Université de Technologie de Compiègne, France.
Title: Fusion of heterogeneous deep neural networks with belief functions
Abstract: to be announced.
To accommodate for the uncertainties surrounding travel possibilities due to the COVID-19 pandemic, participants have two options to attend the conference: either online or onsite.
The event will take place at the Sorbonne Center for Artificial Intelligence (SCAI). There are multiple ways to arrive to the conference site: on subway (Metro lines 7 or 10), by taxi, or by bus.
The registration details and procedure will be announced below, later in the Spring of 2022.
The payment method will be online payment by credit card. In addition, for French participants there will be an option to pay by CNRS purchase order ("bon de commande CNRS").