Graph Wavelet Neural Network Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng ICLR 2019 Supervised Community Detection with Line Graph Neural Networks Zhengdao Chen, Xiang Li, Joan Bruna ICLR 2019 Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera, ...
Reasoning is a very important research topic forhigh-levelartificial intelligence and the reasoning process in human brain is almost based on the graph which is extracted from daily experience. The standard neural networks have shown the ability to generate synthetic images and documents by learning t...
In this study we use the DCRNN model19architecture to explore the spatio-temporal relationships of brain dynamics in resting state fMRI. An overview of the model structure is provided in Fig.1. To learn the temporal dependencies of the BOLD signal, recurrent neural networks (RNNs) with sequence...
Few-Shot Learning with Graph Neural Networks Victor Garcia, Joan Bruna ICLR 2018 Neural Relational Inference for Interacting Systems Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard Zemel ICML 2018 Brain Signal Classification via Learning Connectivity Structure Soobeom Jang, Seong-Eun ...
To address this issue, we propose a Customized Relationship Graph Neural Network (CRGNN) that can bridge the gap between the graph structure and the downstream task. The proposed method can dynamically learn the optimal brain networks/graphs for each task. Specifically, we design a block that ...
(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...
比如提取特征进行分析。具体例子可以是，事件在社交网络上的传播，脑信号在 Brain connectivity network上...
基于历史上的神经图灵机[8]、可微神经计算机[9]等神经执行器(neural executors)的成功,受益于现在广为使用的各种图机器学习工具包,2020 年发表的一些研究工作从理论上探究了神经执行器的缺陷[5,10,11],提出了一些基于 GNN 的强大的新推理架构[12-15],并且在神经推理任务上具有完美的泛化性能[16]。在 2021 年...
近10年来全球各国都在脑模拟研究上进行了大规模布局,无论是欧盟脑计划、美国脑计划的发展、还是日本Brain/MINDS计划,中国脑计划的出台,都预示着我们正站在这历史的交叉点上。 用图计算构建脑仿真 脑仿真本身,并不新鲜。自1943年的人工神经元模型,到如今的脉冲神经网络,都为脑仿真迈出了结实的步伐。然而,技术的...
with them. In recent years, systems based on variants of graph neural networks such as graph convolutional network (GCN), graph attention network (GAT), gated graph neural network (GGNN) have demonstrated ground-breaking performance on many tasks mentioned above. In this survey, we provide a ...