Hybrid Conferencee

International Conference on Probabilistic Approaches in Machine Learning (ICPAPML - 27)

17th - 18th June 2027 | Stavanger, Norway
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Expand the Academic Reach of Your Research - a Q1-ranked and Scopus-indexed journal publication opportunity

Journal consideration and publication are subject to editorial review, peer review and applicable journal policies.

Conference Notifications:

"Be sure to check this section regularly for all Research Plus International Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Stavanger. 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 Stavanger 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 Stavanger conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Stavanger, 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 Stavanger."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICPAPML 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
Probabilistic models in machine learning
02
Bayesian methods for machine learning
03
Stochastic processes in AI applications
04
Probabilistic graphical models in ML
05
Uncertainty quantification in machine learning
06
Applications of Bayesian networks
07
Probabilistic approaches to deep learning
08
Statistical learning theory and applications
09
Reinforcement learning with probabilistic models
10
Probabilistic methods for natural language processing
11
Machine learning for predictive analytics
12
Ensemble methods in probabilistic learning
13
Probabilistic models for time series analysis
14
Applications of Markov models in ML
15
Probabilistic reasoning in AI systems
16
Statistical methods for model evaluation
17
Machine learning with incomplete data
18
Probabilistic approaches to computer vision
19
Applications of probabilistic models in healthcare
20
Probabilistic methods for anomaly detection