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
Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs
Wei Wang, Zhichao Hou, Xiaorui Liu, Xinxia Peng
Advances in Photoacoustic Imaging Reconstruction and Quantitative Analysis for Biomedical Applications
Lei Wang, Weiming Zeng, Kai Long, Hongyu Chen, Rongfeng Lan, Li Liu, Wai Ting Siok, Nizhuan Wang
DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads
Qidong Zhao, Hao Wu, Yuming Hao, Zilingfeng Ye, Jiajia Li, Xu Liu, Keren Zhou
Building Multi-Agent Copilot towards Autonomous Agricultural Data Management and Analysis
Yu Pan, Jianxin Sun, Hongfeng Yu, Joe Luck, Geng Bai, Nipuna Chamara, Yufeng Ge, Tala Awada
Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications
Matthew Werenski, Brendan Mallery, Shuchin Aeron, James M. Murphy
Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements
Isamu Isozaki, Manil Shrestha, Rick Console, Edward Kim
On the analysis of saturated pressure to detect fatigue
Marcos Faundez-Zanuy, Josep Lopez-Xarbau, Moises Diaz, Manuel Garnacho-Castaño
Development of CODO: A Comprehensive Tool for COVID-19 Data Representation, Analysis, and Visualization
Biswanath Dutta, Debanjali Bain