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Call For Papers

The ICBNPR bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Probability Theory, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Bayesian networks in decision making
  • Probabilistic reasoning in AI systems
  • Applications of Bayesian inference
  • Graphical models and their applications
  • Bayesian methods in machine learning
  • Causal inference using Bayesian networks
  • Dynamic Bayesian networks applications
  • Bayesian approaches to data fusion
  • Probabilistic programming languages
  • Bayesian statistics in clinical trials
  • Applications in natural language processing
  • Bayesian methods for big data
  • Hierarchical Bayesian modeling techniques
  • Bayesian optimization in engineering
  • Uncertainty quantification in Bayesian analysis
  • Bayesian methods in environmental science
  • Ethical considerations in Bayesian research
  • Bayesian networks in social networks
  • Applications in financial forecasting
  • Future directions in Bayesian research

Evaluation

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.