Score Prediction

Score prediction, the task of accurately estimating numerical scores based on various input data, is a rapidly evolving field with applications across diverse domains. Current research focuses on developing sophisticated models, including graph neural networks, transformers, and recurrent neural networks, to improve prediction accuracy and address challenges like data imbalance and uncertainty quantification. These advancements are impacting fields ranging from educational assessment and medical diagnosis to drug discovery and image quality assessment, enabling more efficient and reliable analysis of complex data. The emphasis is on creating robust and generalizable models that can handle diverse data types and account for inherent uncertainties in predictions.