从负样本的角度来看,论文提出了一种扰动策略,以生成挑战性负样本,以充分探索模态之间的相关性,并确保每个模态在学习表征中的有效贡献。 参考文献:Multi-modal Graph Contrastive Learning for Micro-video Recommendation
Wei Y., Wang X., Nie L., He X., Hong R. and Chua T. MMGCN: Multi-modal graph convolution network for personalized recommendation of micro-video. MM, 2019. 概 推荐领域里比较早的多模态方法. 符号说明 UU, user set; II, item set; ...
P., Do, L., and de With, P. H. N. (2013). Flexible multi-modal graph-based segmentation. In Advanced Concepts for Intelligent Vision Systems: 15th International Conference, ACIVS 2013, Poznan´, Poland, October 28-31, 2013. Proceedings, pages 492-503. Springer International Publishing....
基于图神经网络的消息传递思想,我们设计了一个多模态图卷积网络(Multi-modal Graph Convolution Network,MMGCN)框架,该框架可以生成用户和微视频特定模态的表征,以更好地捕捉用户的偏好。具体地说,我们在每个模态上构造一个用户-项目二分图(bipartite graph),并用其邻接节点的拓扑结构和特征来丰富每个节点的表征。通过...
可以看到Graph Sage层对某个结点的更新就是不断将其邻接结点的信息融合进来,Wm是Graph Sage层本身的权重,Ws是共享权重,在第一个encoder里是一个可学习权重,在后面两个encoder里是一个全1的矩阵。 SAGPool层: 是一种分层池化的结构(类似MIL中的分层池化层)。这里用了两种池化方法,图上方用最大池化,图下方的残差...
Entity Alignment Knowledge Graphs Multi-modal Entity Alignment Multi-modal Knowledge Graph Datasets Edit MMKG Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods...
prior knowledge, oversee the training of robot systems, and curtail training costs and expenses. This is illustrated in Fig.1. When finding the target object "bed", the agent resorts to the LLMs to find the most relevant graph node (shown as circle) based on the observation and target ...
This repository contains the code and data for the paper "Multi-Modal Graph Neural Networks for Localized Off-Grid Weather Forecasting". - Earth-Intelligence-Lab/LocalizedWeatherGNN
MMGCN (by default) proposed in MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video, ACM MM2019. Usage: --model_name='MMGCN' VBPR proposed in VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback, AAAI2016. Usage: --model_name 'VBPR' ACF propo...
Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Chencheng Zhang, V. Vardhanabhuti, Dongsheng Li, Lili Qiu NPJ Parkinson's Disease|De...