Nature Reviews Methods Primersthanks Jiliang Tang; Siddhartha Mishra, who co-reviewed with Konstantin Rusch; and Rex Ying, who co-reviewed with Tinglin Huang, for their contribution to the peer review of this work. Additional information
From raw detector activations to reconstructed particles, data at the Large Hadron Collider (LHC) are sparse, irregular, heterogeneous and highly relational in nature. Graph neural networks (GNNs), a class of algorithms belonging to the rapidly growing field of geometric deep learning (GDL), are ...
An invariant l = 0 NequIP network, however, displays a similar log-log slope to other methods, suggesting that it is indeed the equivariant nature of NequIP that allows for the change in learning behavior. Further increasing the rotation order l beyond l = 1 again only shifts the...
Given the complex nature of graph structure, graph measures are often used to characterize graphs. In this paper, we focus on one global graph measure, average path length, and one local graph measure, clustering coefficient. Notably, these two measures are widely used in network science (Watts...
Given the complex nature of graph structure, graph measures are often used to characterize graphs. In this paper, we focus on one global graph measure, average path length, and one local graph measure, clustering coefficient. Notably, these two measures are widely used in network science (Watts...
Self-organizing neural network that discovers surfaces in random dot stereograms. Nature, 355(6356):161–163, 1992. [46] Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, and R Devon Hjelm. Mine: mutual information neural estimation. ...
1) Human DLPFC: The primary source: https://www.nature.com/articles/s41593-020-00787-0; the pre-processed source: https://github.com/LieberInstitute/spatialLIBD. 2) Human breast cancer: The primary source: https://www.10xgenomics.com/resources/datasets/human-breast-cancer-block-a-section-...
A Federated Graph Neural Network Framework for Privacy-Preserving Personalizationwww.researchsquare.com/article/rs-1191595/v1 论文支撑材料(图表+算法): Nature_fedgnn_supplementassets.researchsquare.com/files/rs-1191595/v1/71153119f664ba828806b611.pdf 分支领域: Information Retrieval (cs.IR) 论文...
Although deep learning (DL) models for Protein–Protein Interaction (PPI) prediction have been studied extensively, it has not yet been developed for simulating the natural PPI hierarchy. Here, we suggest HIGH-PPI, a hierarchical graph neural network, for accurate and interpretable PPI prediction. ...
(GGNN) have demonstrated ground-breaking performance on many tasks mentioned above. In this survey, we provide a detailed review over existing graph neural network models, systematically categorize the applications, and propose four open problems for future research.大量的学习任务需要处理包含丰富元素间...