A Vegetable-Price Forecasting Method Based on Mixture of Experts by Chenyun Zhao, Xiaodong Wang, Anping Zhao, Yunpeng Cui, Ting Wang, Juan Liu, Ying Hou, Mo Wang, Li Chen, Huan Li, Jinming Wu, Tan Sun

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Mixture of Experts Framework Based on Soft Actor-Critic Algorithm for Highway Decision-Making of Connected and Automated Vehicles by Fuxing Yao, Chao Sun, Bing Lu, Bo Wang, Haiyang Yu

“…This paper proposes a Mixture of Expert method (MoE) based on Soft Actor-Critic (SAC), where the upper-level discriminator dynamically decides whether to activate the lower-level DRL expert or the heuristic expert based on the features of the input state. …”
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MoE-NuSeg: Enhancing nuclei segmentation in histology images with a two-stage Mixture of Experts network by Xuening Wu, Yiqing Shen, Qing Zhao, Yanlan Kang, Wenqiang Zhang

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Simultaneous estimation of multiple soil properties from vis-NIR spectra using a multi-gate mixture-of-experts with data augmentation by Xiaoqing Wang, Mei-Wei Zhang, Ya-Nan Zhou, Lingli Wang, Ling-Tao Zeng, Yu-Pei Cui, Xiao-Lin Sun

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Research on Predicting Super-Relational Data Links for Mine Hoists Within Hyper-Relational Knowledge Graphs by Xiaochao Dang, Xiaoling Shu, Fenfang Li, Xiaohui Dong

“…This paper proposes the HyLinker model, designed to improve the representation of entities and relations through modular components, including an entity neighbor aggregator, a relation qualifier aggregator, MoE-LSTM (Mixture of Experts Long Short-Term Memory), and a convolutional bidirectional interaction module. …”
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Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features by Weitong Guo, Qian He, Ziyu Lin, Xiaolong Bu, Ziyang Wang, Dong Li, Hongwu Yang

“…To tackle this challenge, we propose a Mixture-of-Experts (MoE) method that integrates speaker-related and emotion-related features for depression recognition. …”
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