Zobrazeno 1 - 10
of 5 477
pro vyhledávání: '"Won-Yong So"'
Autor:
Ying Wen, Chayanee Chairattanawat, Kieu Thi Xuan Vo, Jiayou Liu, Jie Zhang, Ting Pan, Do-Young Kim, Enrico Martinoia, Chun-Yan Zhong, Mao-Hui Wang, Jong-Seong Jeon, Won-Yong Song
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Rice is the major source of arsenic (As) intake in humans, as this staple crop readily accumulates As in the grain. Identifying the genes and molecular mechanisms underlying As accumulation and tolerance is a crucial step toward developing rice with
Externí odkaz:
https://doaj.org/article/c1a8125ab3724daf922814914850c7c9
Heterogeneous graph neural networks (HGNNs) have significantly propelled the information retrieval (IR) field. Still, the effectiveness of HGNNs heavily relies on high-quality labels, which are often expensive to acquire. This challenge has shifted a
Externí odkaz:
http://arxiv.org/abs/2409.06323
Collaborative filtering (CF) remains essential in recommender systems, leveraging user--item interactions to provide personalized recommendations. Meanwhile, a number of CF techniques have evolved into sophisticated model architectures based on multi
Externí odkaz:
http://arxiv.org/abs/2409.05878
Cross-domain recommendation (CDR) extends conventional recommender systems by leveraging user-item interactions from dense domains to mitigate data sparsity and the cold start problem. While CDR offers substantial potential for enhancing recommendati
Externí odkaz:
http://arxiv.org/abs/2407.12374
Autor:
Shin, Yong-Min, Shin, Won-Yong
As one of popular quantitative metrics to assess the quality of explanation of graph neural networks (GNNs), fidelity measures the output difference after removing unimportant parts of the input graph. Fidelity has been widely used due to its straigh
Externí odkaz:
http://arxiv.org/abs/2406.11504
The self-attention mechanism has been adopted in several widely-used message-passing neural networks (MPNNs) (e.g., GATs), which adaptively controls the amount of information that flows along the edges of the underlying graph. This usage of attention
Externí odkaz:
http://arxiv.org/abs/2406.04612
Publikováno v:
PLoS ONE, Vol 17, Iss 1, p e0263427 (2022)
[This corrects the article DOI: 10.1371/journal.pone.0252899.].
Externí odkaz:
https://doaj.org/article/3fda1f64b9cc4ab5a019d23cff041553
Publikováno v:
Cells, Vol 11, Iss 17, p 2741 (2022)
Arsenic (As) is a toxic metalloid for all living organisms and can cause serious harm to humans. Arsenic is also toxic to plants. To alleviate As toxicity, all living organisms (from prokaryotes to higher plants) have evolved comprehensive mechanisms
Externí odkaz:
https://doaj.org/article/e356c8adf7de45c7b390c883ddc7e138
A series of graph filtering (GF)-based collaborative filtering (CF) showcases state-of-the-art performance on the recommendation accuracy by using a low-pass filter (LPF) without a training process. However, conventional GF-based CF approaches mostly
Externí odkaz:
http://arxiv.org/abs/2404.14243
A recent study has shown that diffusion models are well-suited for modeling the generative process of user-item interactions in recommender systems due to their denoising nature. However, existing diffusion model-based recommender systems do not expl
Externí odkaz:
http://arxiv.org/abs/2404.14240