The International Research Conference Aims and Objectives
The International Research Conference is a federated organization dedicated to bringing together a significant number of diverse scholarly events for presentation
within the conference program. Events will run over a span of time during the conference depending on the number and length of the presentations.
With its high quality, it provides an exceptional value for students, academics and industry researchers.
International Conference on Bayesian Machine Learning
aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of
Bayesian Machine Learning.
It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations,
trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Bayesian Machine Learning.
Call for Contributions
Prospective authors are kindly encouraged to contribute to and help shape the conference through submissions of their research abstracts, papers and e-posters.
Also, high quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or
theoretical work in all areas of Bayesian Machine Learning are cordially invited for presentation at the conference.
The conference solicits contributions of abstracts, papers and e-posters that address themes and topics of the conference, including figures, tables and references of
novel research materials.
Guidelines for Authors
Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers.
Downloadable versions of the check list for
Full-Text Papers and
Abstract Papers.
Please refer to the
Paper Submission Guideline,
Abstract Submission Guideline and
Author Information
before submitting your paper.
Conference Proceedings
All submitted conference papers will be blind peer reviewed by three competent reviewers.
The peer-reviewed conference proceedings are indexed in the Open Science Index,
Google Scholar,
Semantic Scholar,
Zenedo,
BASE,
WorldCAT,
Sherpa/RoMEO,
and other index databases. Impact Factor Indicators.
Special Journal Issues
19. International Conference on Bayesian Machine Learning has teamed up with the Special Journal Issue on
Bayesian Machine Learning.
A number of selected high-impact full text papers will also be considered for the special journal issues.
All submitted papers will have the opportunity to be considered for this Special Journal Issue.
The paper selection will be carried out during the peer review process as well as at the conference presentation stage.
Submitted papers must not be under consideration by any other journal or publication.
The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly.
Selected full-text papers will be published online free of charge.
Conference Sponsor and Exhibitor Opportunities
The Conference offers the opportunity to become a conference sponsor or exhibitor.
To participate as a sponsor or exhibitor, please download and complete the
Conference Sponsorship Request Form.
Selected Papers
-
Enhancing Predictive Accuracy in Pharmaceutical Sales Through an Ensemble Kernel Gaussian Process Regression Approach
Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf
-
Networked Implementation of Milling Stability Optimization with Bayesian Learning
C. Ramsauer, J. Karandikar, D. Leitner, T. Schmitz, F. Bleicher
-
A Generalized Sparse Bayesian Learning Algorithm for Near-Field Synthetic Aperture Radar Imaging: By Exploiting Impropriety and Noncircularity
Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle
-
Modelling the Occurrence of Defects and Change Requests during User Acceptance Testing
Kevin McDaid, Simon P. Wilson
-
Choosing Search Algorithms in Bayesian Optimization Algorithm
Hao Wu, Jonathan L. Shapiro
Conference venue information will be released soon.
Bayesian learning
Bayesian methods
Bayesian machine learning
Bayesian optimization for machine learning
Bayesian learning theory applied to human cognition
Probabilistic modeling and bayesian inference
Bayesian belief network learning
Bayesian network classifiers
Bayesian cognitive science
Bayesian cognitive modeling
Bayesian inference and cognitive modeling
Computational level of analysis
Bayesian approaches to brain function
Bayes rule in perception, action and cognition
Bayesian modeling of human concept learning
Bayesian learning theory applied to human cognition
Bayesian models of cognition
Bayesian analysis of cognitive models
Bayesian models of cognitive development
| Abstracts/Full-Text Paper Submission Deadline |
|
November 28, 2024 |
| Notification of Acceptance/Rejection |
|
December 12, 2024 |
| Final Paper (Camera Ready) Submission & Early Bird Registration Deadline |
|
September 30, 2025 |
| Conference Dates |
|
October 28-29, 2025 |
