Registration summary
ConferenceICBPIM
ModeStandard / Physical
ParticipationListener
Registration fee$135.00
Bank charges (5.8%)$7.83
Total payable$142.83
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICBPIM conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Bayesian Inference Techniques +
This track focuses on the latest methodologies in Bayesian inference, emphasizing novel approaches to prior and posterior distributions. Researchers are encouraged to present their findings on improving inference accuracy and computational efficiency.
02 Statistical Modeling with Bayesian Frameworks +
This session invites contributions that explore the application of Bayesian frameworks in statistical modeling across various domains. Discussions will include model selection, validation, and the integration of prior knowledge.
03 Bayesian Networks and Their Applications +
This track highlights the development and application of Bayesian networks in complex systems. Participants are encouraged to share innovative uses of these networks in fields such as bioinformatics, social sciences, and artificial intelligence.
04 Monte Carlo Methods in Bayesian Analysis +
This session will delve into the use of Monte Carlo methods for Bayesian analysis, focusing on advancements and practical applications. Researchers are invited to present their work on improving sampling techniques and computational strategies.
05 Probabilistic Inference in Machine Learning +
This track examines the intersection of probabilistic inference and machine learning, highlighting Bayesian approaches to model learning and decision-making. Contributions that address challenges in scalability and interpretability are particularly welcome.
06 Markov Chain Monte Carlo Techniques +
This session is dedicated to the exploration of Markov Chain Monte Carlo (MCMC) techniques in Bayesian statistics. Presenters will discuss innovative algorithms and their applications in high-dimensional parameter spaces.
07 Decision Theory and Bayesian Approaches +
This track focuses on the integration of decision theory with Bayesian inference methods. Contributions that explore risk assessment, utility functions, and decision-making under uncertainty are encouraged.
08 Computational Probability and Algorithm Development +
This session invites discussions on the development of computational algorithms for probabilistic modeling and inference. Researchers are encouraged to share their advancements in efficiency and accuracy in computational probability.
09 Simulation Techniques in Bayesian Statistics +
This track focuses on simulation techniques used in Bayesian statistics, including their implementation and evaluation. Participants are invited to present case studies that demonstrate the effectiveness of these techniques in real-world applications.
10 Prior Distribution Selection and Its Implications +
This session will explore the critical role of prior distribution selection in Bayesian analysis. Researchers are encouraged to discuss methodologies for prior elicitation and the impact of priors on posterior outcomes.
11 Emerging Trends in Bayesian Research +
This track highlights emerging trends and future directions in Bayesian research across various fields. Participants are invited to share innovative ideas and collaborative opportunities that push the boundaries of Bayesian probability and inference.
