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AI Open

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JOURNAL INFORMATION
Publisher KeAi Communications Co.
Open Access YES
Quartile Q1
Citation Count 803
E-ISSN 2666-6510
Categories Artificial Intelligence, Computer Science Applications, Computer Vision and Pattern Recognition, Human-Computer Interaction, Information Systems
Area Software, Artificial Intelligence, Computer Science Applications
Region Asiatic Region
Country China
SCOPE

AI Open is a freely accessible platform to share actionable knowledge and forward-thinking perspectives on the theory of artificial intelligence and its applications. The journal welcomes research articles, review papers, perspectives, short communications and technical notes on all aspects of artificial intelligence and its applications.

Topics covered include, but are not limited to:
Deep learning and representation learning
Graph theory and graph mining
Constraints, satisfiability, and search
Knowledge representation, reasoning, and logic
Machine learning and data mining
Knowledge graph and applications
Agent-based and multi-agent systems
Web and knowledge-based information systems
Natural language processing
Image processing and analysis
Uncertainty
Brain-based Learning
Implicit Cognition and Learning


Human Brain Research:
Hot topics in human brain-related health/diseases/social behavior
Brain Connectivity and network modeling
Brain intelligence paradigms
Neuro-informatics
Neuroimaging
Learning and memory
Cognition and behavior
health data analysis and statistics
Neuroimmunology
Sleep behavior
Deep brain stimulation

Summary

  1. AI Open is published by KeAi Communications Co.
  2. It is an oppen access journal
  3. The Subject Area : Software, Artificial Intelligence, Computer Science Applications

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Latest Articles published

Last updated: 10/09/2024

Wave2Graph: Integrating spectral features and correlations for graph-based learning in sound waves


Last updated: 06/09/2024

Relation-aware deep neural network enables more efficient biomedical knowledge acquisition from massive literature


Last updated: 18/08/2024

MindLLM: Lightweight large language model pre-training, evaluation and domain application


Last updated: 19/03/2024

Adaptive negative representations for graph contrastive learning


Last updated: 17/03/2024

Label-aware debiased causal reasoning for Natural Language Inference


Last updated: 28/02/2024

An ecosystem for personal knowledge graphs: A survey and research roadmap


Last updated: 23/02/2024

Boosting graph search with attention network for solving the general orienteering problem


Last updated: 11/02/2024

CPT: Colorful Prompt Tuning for pre-trained vision-language models


Last updated: 28/01/2024

PM2.5 forecasting under distribution shift: A graph learning approach


Last updated: 31/12/2023

Enhancing neural network classification using fractional-order activation functions