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
Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baseline
Siddhesh Khandelwal, Anirudth Nambirajan, Behjat Siddiquie, Jayan Eledath, Leonid Sigal
The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation
Kushal Arora, Timothy J. O'Donnell, Doina Precup, Jason Weston, Jackie C. K. Cheung
Weakly-supervised Representation Learning for Video Alignment and Analysis
Guy Bar-Shalom, George Leifman, Michael Elad, Ehud Rivlin
Futuristic Variations and Analysis in Fundus Images Corresponding to Biological Traits
Muhammad Hassan, Hao Zhang, Ahmed Fateh Ameen, Home Wu Zeng, Shuye Ma, Wen Liang, Dingqi Shang, Jiaming Ding, Ziheng Zhan, Tsz Kwan Lam, Ming Xu, Qiming Huang, Dongmei Wu, Can Yang Zhang, Zhou You, Awiwu Ain, Pei Wu Qin
GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
Ali Pourramezan Fard, Mohammad H. Mahoor, Sarah Ariel Lamer, Timothy Sweeny
Analysis of Biomass Sustainability Indicators from a Machine Learning Perspective
Syeda Nyma Ferdous, Xin Li, Kamalakanta Sahoo, Richard Bergman