Narrative Review
Narrative reviews synthesize existing research to provide a comprehensive overview of a specific topic, aiming to identify key trends, gaps, and future research directions. Current research focuses on applying narrative reviews across diverse fields, employing various model architectures like graph neural networks, large language models, and diffusion models to analyze complex data and improve model interpretability and efficiency. This approach is crucial for advancing scientific understanding and informing the development of practical applications in areas such as medicine, engineering, and manufacturing.
Papers
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Continuous-Time Analog Filters for Audio Edge Intelligence: Review on Circuit Designs
Kwantae Kim, Shih-Chii Liu
Reservoir Computing in robotics: a review
Paolo Baldini
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data
Shohreh Deldari, Hao Xue, Aaqib Saeed, Jiayuan He, Daniel V. Smith, Flora D. Salim