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
An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks
Yash Bingi, Yiqiao Yin
Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock
Dengxin Huang
Are we describing the same sound? An analysis of word embedding spaces of expressive piano performance
Silvan David Peter, Shreyan Chowdhury, Carlos Eduardo Cancino-Chacón, Gerhard Widmer
The Art of Defending: A Systematic Evaluation and Analysis of LLM Defense Strategies on Safety and Over-Defensiveness
Neeraj Varshney, Pavel Dolin, Agastya Seth, Chitta Baral
Why is the User Interface a Dark Pattern? : Explainable Auto-Detection and its Analysis
Yuki Yada, Tsuneo Matsumoto, Fuyuko Kido, Hayato Yamana