中国计算机学会(CCF)推荐学术会议-C(人工智能):IJCNN 2026

IJCNN 2026

The annual IEEE/INNS IJCNN is the premier international conference in the area of neural networks theory, analysis and applications. Since its inception, IJCNN has been playing a leading role in promoting and facilitating interaction among researchers and practitioners, and dissemination of knowledge in neural networks and related facets of machine learning.

This year IEEE/INNS IJCNN 2026 is a part of the WCCI2026. IJCNN 2026 will represent a unique meeting point for scientists and engineers, both from academia and industry, to interact and discuss the latest enhancements and innovations in the field.

重要信息

CCF推荐:C(人工智能)

录用率:38.7%(2142/5526,2025年)

时间地点:2026年6月21日-马斯特里赫特·荷兰

截稿时间:2026年1月31日

大会官网:https://attend.ieee.org/wcci-2026/

Call for Papers

Brain-machine Interfaces

Cognitive Models

Collective & Ensemble Intelligence

Computational Neuroscience

Dynamic Neural Networks

Efficient and Tiny Neural Networks

Ethics and Regulation in AI

Generative AI Models

Graph Neural Networks

Industrial applications

Interpretable and Explainable AI

Large Language Models

Large-Scale Neural Networks

Mixture of Experts

Modular Neural Networks

Neural Engineering

Neural Network Applications

Neural Networks for Sciences

Neuromorphic Systems

Neurosymbolic AI

Perceptual Neural Networks

Physics-inspired Neural Networks and Neural Operators

Quantum Neural Networks

Reinforcement Learning

Representation & Reasoning

Reservoir & Echo-State Networks

Spiking Neural Networks

Theory of Neural Networks

Transformer Networks

Trustworthy and Reliable AI

Unsupervised Learning

Submission Format

All papers must be submitted using the IEEE conference proceedings template with body text in 10pt type. LaTeX users must use \documentclass[10pt,conference]{IEEEtran}.

Page limitations

Full papers: papers of up to 6 pages. A maximum of two extra content pages per full paper is allowed (i.e, up to 8 pages), at an additional charge per extra page as specified in the registration page.

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