IEEE IJCNN 2027
Machine Learning, Artificial Intelligence and conference
About
IJCNN covers neural-network foundations and intelligent applications, including continual and adaptive learning, forgetting mitigation, representation learning, explainability, neuromorphic computation, computational neuroscience and multimodal models. Research papers connect theoretical methods with applications across science and engineering.
Review is double-blind. Standard submissions use six IEEE-format pages; up to four extra pages incur fees. Accepted authors must submit final papers and pay the corresponding registration fees by 12 April 2027, 23:59 AoE. Remote authors may supply prerecorded presentations, but the conference does not offer live remote attendance.
Topics
- neural-network foundations
- adaptive learning
- forgetting mitigation
- representation learning
- explainability
- neuromorphic computation
- Computational Neuroscience
- multimodal models
- intelligent applications
People
Clemson University, SC
Sapienza University of Rome
Singapore Management University (SMU) and Agency for Science, Technology and Research (A*STAR)
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Upcoming talks in Machine Learning
All seminarsAI That Thinks Differently: Seeing, Understanding, and Trusting Visual Data in the Age of Foundation Models
Oct 28, 2026Manoranjan PaulData-Driven Interpretable Dynamical Systems Models for Neuroscience & Psychiatry
Oct 21, 2026Manuel Brenner