Zobrazeno 1 - 10
of 282 317
pro vyhledávání: '"An Tai"'
Autor:
Yong Suk Jo, Chin Kook Rhee, Hyoung Kyu Yoon, Chan Kwon Park, Jeong Uk Lim, An Tai Joon, Jung Hur
Publikováno v:
Journal of Inflammation, Vol 19, Iss 1, Pp 1-10 (2022)
Abstract Background Features of asthma and chronic obstructive pulmonary disease (COPD) can coexist in the same patient, in a condition termed asthma– chronic obstructive pulmonary disease overlap (ACO). ACO is heterogeneous condition exhibiting va
Externí odkaz:
https://doaj.org/article/f8946a656b1142bf8e1f86d5a44a9f22
Autor:
Zhao, Penghai, Xing, Qinghua, Dou, Kairan, Tian, Jinyu, Tai, Ying, Yang, Jian, Cheng, Ming-Ming, Li, Xiang
As the academic landscape expands, the challenge of efficiently identifying potentially high-impact articles among the vast number of newly published works becomes critical. This paper introduces a promising approach, leveraging the capabilities of f
Externí odkaz:
http://arxiv.org/abs/2408.03934
Autor:
Kahle, Leonid, Minisini, Benoit, Bui, Tai, First, Jeremy T., Buda, Corneliu, Goldman, Thomas, Wimmer, Erich
Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set.
Externí odkaz:
http://arxiv.org/abs/2408.03058
Missing data in tabular dataset is a common issue as the performance of downstream tasks usually depends on the completeness of the training dataset. Previous missing data imputation methods focus on numeric and categorical columns, but we propose a
Externí odkaz:
http://arxiv.org/abs/2408.02128
Many head pose estimation (HPE) methods promise the ability to create full-range datasets, theoretically allowing the estimation of the rotation and positioning of the head from various angles. However, these methods are only accurate within a range
Externí odkaz:
http://arxiv.org/abs/2408.01566
Autor:
Pang, Jinhui, Lin, Changqing, Hao, Xiaoshuai, Yin, Rong, Wang, Zixuan, Zhang, Zhihui, He, Jinglin, Sheng, Huang Tai
Continual graph learning (CGL) is an important and challenging task that aims to extend static GNNs to dynamic task flow scenarios. As one of the mainstream CGL methods, the experience replay (ER) method receives widespread attention due to its super
Externí odkaz:
http://arxiv.org/abs/2407.19429
Autor:
Chinta, Sribala Vidyadhari, Wang, Zichong, Yin, Zhipeng, Hoang, Nhat, Gonzalez, Matthew, Quy, Tai Le, Zhang, Wenbin
The integration of Artificial Intelligence (AI) into education has transformative potential, providing tailored learning experiences and creative instructional approaches. However, the inherent biases in AI algorithms hinder this improvement by unint
Externí odkaz:
http://arxiv.org/abs/2407.18745
Autor:
Towers, Mark, Kwiatkowski, Ariel, Terry, Jordan, Balis, John U., De Cola, Gianluca, Deleu, Tristan, Goulão, Manuel, Kallinteris, Andreas, Krimmel, Markus, KG, Arjun, Perez-Vicente, Rodrigo, Pierré, Andrea, Schulhoff, Sander, Tai, Jun Jet, Tan, Hannah, Younis, Omar G.
Gymnasium is an open-source library providing an API for reinforcement learning environments. Its main contribution is a central abstraction for wide interoperability between benchmark environments and training algorithms. Gymnasium comes with variou
Externí odkaz:
http://arxiv.org/abs/2407.17032
Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians a
Externí odkaz:
http://arxiv.org/abs/2407.16014
Graph-level anomaly detection is significant in diverse domains. To improve detection performance, counterfactual graphs have been exploited to benefit the generalization capacity by learning causal relations. Most existing studies directly introduce
Externí odkaz:
http://arxiv.org/abs/2407.13251