Holistic Approach
A "holistic approach" in research emphasizes comprehensive consideration of all relevant factors and their interrelationships, aiming for more accurate and robust solutions compared to methods focusing on isolated aspects. Current research focuses on developing holistic models across diverse fields, including computer vision (using graph transformers and autoencoders), natural language processing (leveraging large language models and knowledge graphs), and medical applications (integrating machine learning with biological data). This integrated approach enhances model performance, improves explainability, and addresses biases, leading to more reliable and impactful results in various scientific and practical applications.
Papers
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