In contrastive learning module, target nodeand subgraph are sampled from both views to construct multi-scale contrast combinations. With intra- and intre- view contrastive strategy, we can effectively capture both local and global information of anomaly nodes. In attribute reconstruction module, masked...
work related to the heterogeneous network embedding technique is introduced; “Preliminary” section describes some preliminaries; “Multi-view heterogeneous graph contrastive learning” section describes the implementation of the multi-view contrastive learning for heterogeneous network embedding; “Multi-view ...
which can effectively integrate multi-scale information for learning. In contrast to existing methods that rely heavily on single-scale information, MUSE effectively addresses the optimization imbalance in multi-scale learning through mutual supervision and iterative optimization...
Fang Y, Zhang Q, Zhang N, Chen Z, Zhuang X, Shao X, Fan X, Chen H (2023) Knowledge graph-enhanced molecular contrastive learning with functional prompt. Nat Mach Intell 1–12 Öztürk H, Özgür A, Ozkirimli E (2018) Deepdta: deep drug–target binding affinity prediction. Bioinforma...
Video Multimodal Entity Linking via Multi-Perspective Enhanced Subgraph Contrastive Network Video Multimodal Entity Linking (VMEL) is a task to link entities mentioned in videos to entities in multimodal knowledge bases. However, current entity li... H Li,Y Yue,X Man,... - 《International Journal...
Subsequently, this node is removed, along with its neighboring nodes recursively, until a predetermined proportion of the subgraph is eliminated (0.2 for the Davis dataset and 0.1 for the KIBA dataset) while maintaining the affinity scores of drug–target pairs and the Morgan and Avalon finger...
For example, objects captured by a low-angle camera typically have large scale variations even with subtle changes in their y-coordinates while ob- jects in a top-down view do not have any correlation be- tween their locations and sizes. Therefore, the features in 2D image space should be...
To address this challenge, we propose a novel framework called the multi-perspective enhanced Subgraph Contrastive Network (SCMEL) and construct a VMEL dataset named SceneMEL, based on tourism domain. We first integrate textual, auditory and visual modal contexts of videos to generate a ...
only large-scale training samples can help models achieve great performance. The performance drastically changes with the variation in the size of the training sample. Unfortunately, data labelling is expensive and time-consuming. These graph-based deep learning models that rely on large-scale labelled...
Spatially resolved transcriptomics (SRT) technology enables us to gain novel insights into tissue architecture and cell development, especially in tumors. However, lacking computational exploitation of biological contexts and multi-view features severely