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
Building Expressive and Tractable Probabilistic Generative Models: A Review
Sahil Sidheekh, Sriraam Natarajan
MobilityDL: A Review of Deep Learning From Trajectory Data
Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld, Krzysztof Janowicz
In-Bed Pose Estimation: A Review
Ziya Ata Yazıcı, Sara Colantonio, Hazım Kemal Ekenel