Cost Prediction

Cost prediction research aims to accurately estimate future expenses across diverse domains, from healthcare and shipping to robotics and AI model deployment. Current efforts focus on developing sophisticated models, including transformer networks and graph neural networks, to capture complex relationships within data and improve prediction accuracy beyond traditional methods like tree-based models. These advancements are driven by the need for more efficient resource allocation and improved decision-making in various sectors, leading to tangible benefits such as reduced healthcare waste, optimized pricing strategies, and more efficient robotic task planning. Furthermore, research explores robust methods to handle outliers and cost-efficient strategies for utilizing large-scale models.