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
Analysis of Training Object Detection Models with Synthetic Data
Bram Vanherle, Steven Moonen, Frank Van Reeth, Nick Michiels
Hiding speaker's sex in speech using zero-evidence speaker representation in an analysis/synthesis pipeline
Paul-Gauthier Noé, Xiaoxiao Miao, Xin Wang, Junichi Yamagishi, Jean-François Bonastre, Driss Matrouf
An Analysis of Social Biases Present in BERT Variants Across Multiple Languages
Aristides Milios, Parishad BehnamGhader
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression
Xiaoyun Li, Ping Li
Data-driven identification and analysis of the glass transition in polymer melts
Atreyee Banerjee, Hsiao-Ping Hsu, Kurt Kremer, Oleksandra Kukharenko
Climate Policy Tracker: Pipeline for automated analysis of public climate policies
Artur Żółkowski, Mateusz Krzyziński, Piotr Wilczyński, Stanisław Giziński, Emilia Wiśnios, Bartosz Pieliński, Julian Sienkiewicz, Przemysław Biecek
Reconstruction and analysis of negatively buoyant jets with interpretable machine learning
Marta Alvir, Luka Grbčić, Ante Sikirica, Lado Kranjčević
Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification
Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy, Jennifer Merickel, Matt Rizzo, Anuj Sharma
Liability regimes in the age of AI: a use-case driven analysis of the burden of proof
David Fernández Llorca, Vicky Charisi, Ronan Hamon, Ignacio Sánchez, Emilia Gómez
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Theresa Bender, Jacqueline Michelle Beinecke, Dagmar Krefting, Carolin Müller, Henning Dathe, Tim Seidler, Nicolai Spicher, Anne-Christin Hauschild