ISSN: 2666-6510

Editor-in-Chief

Björn W. Schuller

Editorial Board

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 art...

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

Adaptive negative representations for graph contrastive learning

How to generate popular post headlines on social media?

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

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1. Graph neural networks: A review of methods and applications

2. A survey of transformers

3. Pre-trained models: Past, present and future

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Graph neural networks: A review of methods and applications

Pre-trained models: Past, present and future

A survey of transformers

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Call for Papers

Special Issue on Large Language Models for Social Impact (LLMSI)

Submission deadline: 30 October, 2024

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News

AI Open Calls for Reviewers!

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AI Open Calls for Young Editorial Board Members (20-50)!

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AI Open is now indexed in ESCI

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