Graph U-Nets
暂无分享,去创建一个
[1] Joan Bruna,et al. Spectral Networks and Locally Connected Networks on Graphs , 2013, ICLR.
[2] Mathias Niepert,et al. Learning Convolutional Neural Networks for Graphs , 2016, ICML.
[3] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[4] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[5] Yoshua Bengio,et al. The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[6] Hans-Peter Kriegel,et al. Protein function prediction via graph kernels , 2005, ISMB.
[7] Phil Blunsom,et al. A Convolutional Neural Network for Modelling Sentences , 2014, ACL.
[8] Pierre Vandergheynst,et al. Geometric Deep Learning: Going beyond Euclidean data , 2016, IEEE Signal Process. Mag..
[9] Joan Bruna,et al. Deep Convolutional Networks on Graph-Structured Data , 2015, ArXiv.
[10] Samuel S. Schoenholz,et al. Neural Message Passing for Quantum Chemistry , 2017, ICML.
[11] Le Song,et al. Discriminative Embeddings of Latent Variable Models for Structured Data , 2016, ICML.
[12] Jure Leskovec,et al. Predicting multicellular function through multi-layer tissue networks , 2017, Bioinform..
[13] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[14] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[15] S. V. N. Vishwanathan,et al. A Structural Smoothing Framework For Robust Graph Comparison , 2015, NIPS.
[16] Yann LeCun,et al. Stacked What-Where Auto-encoders , 2015, ArXiv.
[17] Pietro Liò,et al. Graph Attention Networks , 2017, ICLR.
[18] P. Dobson,et al. Distinguishing enzyme structures from non-enzymes without alignments. , 2003, Journal of molecular biology.
[19] Nikos Komodakis,et al. Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[21] Max Welling,et al. Modeling Relational Data with Graph Convolutional Networks , 2017, ESWC.
[22] Jonathan Masci,et al. Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[25] Han Zhao,et al. Self-Adaptive Hierarchical Sentence Model , 2015, IJCAI.
[26] Zhengyang Wang,et al. Large-Scale Learnable Graph Convolutional Networks , 2018, KDD.
[27] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] 한보형,et al. Learning Deconvolution Network for Semantic Segmentation , 2015 .
[29] Alán Aspuru-Guzik,et al. Convolutional Networks on Graphs for Learning Molecular Fingerprints , 2015, NIPS.
[30] Yangqing Jia,et al. Deep Convolutional Ranking for Multilabel Image Annotation , 2013, ICLR.
[31] Steven Skiena,et al. DeepWalk: online learning of social representations , 2014, KDD.
[32] Heinrich Müller,et al. SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[33] Jure Leskovec,et al. Hierarchical Graph Representation Learning with Differentiable Pooling , 2018, NeurIPS.
[34] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.
[35] Kaiming He,et al. Mask R-CNN , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[36] Lise Getoor,et al. Collective Classification in Network Data , 2008, AI Mag..
[37] Shuiwang Ji,et al. Efficient and Invariant Convolutional Neural Networks for Dense Prediction , 2017, 2017 IEEE International Conference on Data Mining (ICDM).
[38] Ruslan Salakhutdinov,et al. Revisiting Semi-Supervised Learning with Graph Embeddings , 2016, ICML.
[39] Yixin Chen,et al. An End-to-End Deep Learning Architecture for Graph Classification , 2018, AAAI.
[40] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[41] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.
[42] Sundeep Prabhakar Chepuri,et al. Subsampling for graph power spectrum estimation , 2016, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM).
[43] F. Scarselli,et al. A new model for learning in graph domains , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[44] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Antonio G. Marques,et al. Convolutional Neural Network Architectures for Signals Supported on Graphs , 2018, IEEE Transactions on Signal Processing.
[46] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.