blackout
发表于 2025-3-23 11:40:09
http://reply.papertrans.cn/83/8230/822911/822911_11.png
Shuttle
发表于 2025-3-23 16:25:10
http://reply.papertrans.cn/83/8230/822911/822911_12.png
Common-Migraine
发表于 2025-3-23 19:42:05
Data Entropy-Based Imbalanced Learning,ce among classes in machine learning. However, our recent study challenges this notion. We argue that the bias of classification performance comes from the imbalance of information of classes rather than just that of observations. To reflect the information imbalance of classes, we propose an indica
毕业典礼
发表于 2025-3-24 01:04:48
Analysis of the Changes in Microbial Community During the Fermentation of Feng-Flavour Baijiu,ns of Feng-flavour Baijiu. A total of 133 fungi and 688 bacteria were detected at the genus level. The dominant fungi were . and . while the dominant bacteria are . and . The composition of the dominant microorganism in the fermented grains of Feng-flavour Baijiu was different from other flavor Baij
起草
发表于 2025-3-24 06:01:12
http://reply.papertrans.cn/83/8230/822911/822911_15.png
气候
发表于 2025-3-24 08:15:55
http://reply.papertrans.cn/83/8230/822911/822911_16.png
Hot-Flash
发表于 2025-3-24 12:30:53
http://reply.papertrans.cn/83/8230/822911/822911_17.png
Badger
发表于 2025-3-24 14:57:29
http://reply.papertrans.cn/83/8230/822911/822911_18.png
贵族
发表于 2025-3-24 21:50:48
,Classification of In-Situ Solar Wind Data Measured by Solar Orbiter/SWA-PAS and HIS Using Machine Lnge can now be addressed using modern AI/ML techniques and big data analysis algorithms. In this work, we apply state-of-the-art AI/ML technology on in-situ solar wind measurements made by the Heavy Ion Sensor (HIS) and Proton and Alpha Particle Sensor (PAS) onboard the recent Solar Orbiter mission
epinephrine
发表于 2025-3-24 23:42:19
,Node Classification with Multi-hop Graph Convolutional Network,tructures, and retaining structural and feature information within the node vectors. However, incorporating global structures into the latent representation is frequently overlooked despite being a central focus of many random-walk-based embedding techniques predating the advent of graph neural netw