论文原文链接:[1711.07553] Residual Gated Graph ConvNets (arxiv.org) 摘要 图结构数据,如社交网络、脑功能网络、基因调控网络、通信网络等,引起了人们对将深度学习技术推广到图领域的兴趣。在本文中,我们有兴趣设计可变长度图的神经网络,以解决顶点分类、图分类、图回归和图生成任务等学习问题。现有的大部分工作都...
Graph ConvNets are also 36% more accurate than variational (non-learning) techniques. Finally, the most effective graph ConvNet architecture uses gated edges and residuality. Residuality plays an essential role to learn multi-layer architectures as they provide a 10% gain of performance. 展开 ...
The code 01_residual_gated_graph_convnets_subgraph_matching.ipynb presents an application of the residual gated graph convNets for the problem of sub-graph matching. The code 02_residual_gated_graph_convnets_semisupervised_clustering.ipynb shows another application for the problem of semi-supervised...
convCNPs (Vaughan et al., 2022) / Temperature, precipitation – ✓ Empty Cell CNN1, CNN10 (Bano-Medina, 2020) / Temperature, precipitation 4 ✓ Empty Cell CNN1, CNN10, CNN-PR, CNNdense (Bano-Medina et al., 2020) / Temperature, precipitation 4 ✓ Empty Cell CNN1, CNN10 (Bano...
ConvNeXTV2 (from Facebook AI) released with the paper ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders by Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie. CPM (from Tsinghua University) released with the paper CPM: ...
Chen LC, Papandreou G, Kokkinos I et al (2017) Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans Pattern Anal Mach Intell 40(4):834–848 Google Scholar Dice LR (1945) Measures of the amount of ecologic association be...
273 Fast ConvNets Using Group-Wise Brain Damage. Vadim Lebedev, Victor Lempitsky 相当于是卷积神经元网络的加速,类似于Drop-out,这里估计是相当于整个group的drop-out,也就是直接brain damage了。We revisit the idea of brain damage, i.e. the pruning of the coefficients of a neural network, and su...
Extracting buildings from high-resolution remote sensing images by deep ConvNets equipped with structural-cue-guided feature alignment. Int. J. Appl. Earth Obs. Geoinf. 2022, 113, 102970. [Google Scholar] [CrossRef] Long, J.; Shelhamer, E.; Darrell, T. Fully convolutional networks for ...
The training parameters had 1𝑀1M fewer values than gated convolution (Gated Conv). Finally, we present two automated target-hiding techniques that integrate semantic segmentation with direct target hiding or edge-guided synthesis for remote sensing mapping applications. Keywords: emergency remote ...
In SENets, however, each channel-wise feature value is adaptively readjusted by explicitly modeling interconnection between channels. This is carried out by squeezing the input feature maps to a single number using global average pooling, resulting in a vector of length C, where C is the number...