📚️️Artificial Intelligence

• Fundamental Theories and Methods of Machine Learning 

• Core Technologies of Deep Learning and Neural Networks 

• Large Language Models and Generative AI Technologies 

• Computer Vision and Pattern Recognition 

• Natural Language Processing and Intelligent Interaction 

• Reinforcement Learning and Intelligent Decision Making 

• Explainable AI and Trustworthy Artificial Intelligence 

• Federated Learning and Privacy Computing 

• Edge Intelligence and Model Lightweight Technologies 

• AI Security and Adversarial Defense Technologies

📚️️Representation Learning 

• Mathematical Foundations and Theoretical Frameworks of Representation Learning 

• Self-supervised / Unsupervised Representation Learning 

• Semi-supervised / Weakly-supervised Representation Learning 

• Multimodal / Cross-domain Representation Learning 

• Contrastive Learning and Collaborative Representation Learning 

• Knowledge Representation and Knowledge Graph Embedding 

• Sequential / Graph-structured Data Representation Learning 

• Few-shot / Zero-shot Representation Learning 

• Robust and Explainable Representation Learning 

• Generative Representation Learning Methods

📚️️Fusion Innovation and Application of Artificial Intelligence and Representation Learning

• Large Model Optimization Driven by Representation Learning 

• Fusion Technologies of Representation Learning and Computer Vision 

• Fusion Technologies of Representation Learning and Natural Language Processing 

• Applications of Representation Learning in Multimodal Intelligence 

• Fusion Applications in Smart Healthcare and Bioinformatics 

• Fusion Applications in Smart Manufacturing and Industrial Intelligence 

• Fusion Applications in Autonomous Driving and Intelligent Transportation 

• Fusion Applications in Smart Cities and FinTech 

• Applications in Remote Sensing and Ecological Environment Monitoring 

• Other Innovative Applications in Cross-domain Fusion