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 Hardware Synthesis Strategies for Machine Learning in Collider Trigger and Data Acquisition
Haoyi Jia, Abhilasha Dave, Julia Gonski, Ryan Herbst
Leveraging Computational Pathology AI for Noninvasive Optical Imaging Analysis Without Retraining
Danny Barash, Emilie Manning, Aidan Van Vleck, Omri Hirsch, Kyi Lei Aye, Jingxi Li, Philip O. Scumpia, Aydogan Ozcan, Sumaira Aasi, Kerri E. Rieger, Kavita Y. Sarin, Oren Freifeld, Yonatan Winetraub
Analysis of Generalized Hebbian Learning Algorithm for Neuromorphic Hardware Using Spinnaker
Shivani Sharma, Darshika G. Perera
Precision or Recall? An Analysis of Image Captions for Training Text-to-Image Generation Model
Sheng Cheng, Maitreya Patel, Yezhou Yang
FASSILA: A Corpus for Algerian Dialect Fake News Detection and Sentiment Analysis
Amin Abdedaiem, Abdelhalim Hafedh Dahou, Mohamed Amine Cheragui, Brigitte Mathiak
Normalized Space Alignment: A Versatile Metric for Representation Analysis
Danish Ebadulla, Aditya Gulati, Ambuj Singh
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, 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