General Analysis
General analysis encompasses a broad range of methodologies applied across diverse scientific domains to extract meaningful insights from data. Current research focuses on developing robust and efficient analytical techniques, including the application of machine learning models like convolutional neural networks, graph neural networks, and transformer architectures, as well as statistical methods for data modeling and hypothesis testing. These advancements are improving the accuracy and efficiency of analyses in fields ranging from medical image processing and materials science to social media analysis and autonomous systems, ultimately leading to more reliable scientific findings and improved decision-making in various applications.
Papers
Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective
Mattia Setzu, Silvia Corbara, Anna Monreale, Alejandro Moreo, Fabrizio Sebastiani
Multi-EuP: The Multilingual European Parliament Dataset for Analysis of Bias in Information Retrieval
Jinrui Yang, Timothy Baldwin, Trevor Cohn