Hybrid Conferencee

International Conference on Bayesian Probability and Inference Methods (ICBPIM - 26)

29th - 30th June 2026 | London, UK
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in London. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the London event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the London conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in London, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in London."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICBPIM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Probability Theory, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

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

01
Bayesian inference in complex models
02
Applications of Bayesian probability
03
Bayesian methods in machine learning
04
Hierarchical Bayesian modeling techniques
05
Bayesian networks in decision analysis
06
Bayesian approaches to causal inference
07
Probabilistic programming for Bayesian analysis
08
Bayesian methods in clinical research
09
Applications in environmental statistics
10
Bayesian optimization techniques
11
Bayesian methods for time series analysis
12
Statistical validation of Bayesian models
13
Bayesian methods in finance
14
Applications in social sciences
15
Bayesian approaches to big data
16
Ethics in Bayesian research
17
Emerging trends in Bayesian statistics
18
Bayesian methods for network analysis
19
Future directions in Bayesian inference
20
Case studies in Bayesian applications