See also Graph Convolutional Neural Networks.

*Bai, S.[Song]*,
*Zhang, F.H.[Fei-Hu]*,
*Torr, P.H.S.[Philip H.S.]*,

**Hypergraph convolution and hypergraph attention**,

*PR(110)*, 2021, pp. 107637.

Elsevier DOI
**2011**

Graph learning, Hypergraph learning, Graph neural networks,
Semi-supervised learning
BibRef

*Gama, F.*,
*Isufi, E.*,
*Leus, G.*,
*Ribeiro, A.*,

**Graphs, Convolutions, and Neural Networks: From Graph Filters to
Graph Neural Networks**,

*SPMag(37)*, No. 6, November 2020, pp. 128-138.

IEEE DOI
**2011**

Convolution, Finite impulse response filters,
Autoregressive processes, Network topology, Information filters,
Graphical models
BibRef

*Li, Y.S.[Yan-Sheng]*,
*Chen, R.X.[Rui-Xian]*,
*Zhang, Y.J.[Yong-Jun]*,
*Zhang, M.[Mi]*,
*Chen, L.[Ling]*,

**Multi-Label Remote Sensing Image Scene Classification by Combining a
Convolutional Neural Network and a Graph Neural Network**,

*RS(12)*, No. 23, 2020, pp. xx-yy.

DOI Link
**2012**

BibRef

*Jiang, J.J.[Jun-Jie]*,
*He, Z.X.[Zai-Xing]*,
*Zhang, S.Y.[Shu-You]*,
*Zhao, X.Y.[Xin-Yue]*,
*Tan, J.R.[Jian-Rong]*,

**Learning to transfer focus of graph neural network for scene graph
parsing**,

*PR(112)*, 2021, pp. 107707.

Elsevier DOI
**2102**

Semantic relationship, Graphical focus, Scene graph,
Class imbalance, Image understanding
BibRef

*Ruiz, L.[Luana]*,
*Gama, F.[Fernando]*,
*Ribeiro, A.[Alejandro]*,

**Graph Neural Networks: Architectures, Stability, and Transferability**,

*PIEEE(109)*, No. 5, May 2021, pp. 660-682.

IEEE DOI
**2105**

Training, Stability analysis, Convolution, Neural networks,
Transforms, Strain, Probability distribution, Equivariance,
transferability
BibRef

*Manessi, F.[Franco]*,
*Rozza, A.[Alessandro]*,

**Graph-based neural network models with multiple self-supervised
auxiliary tasks**,

*PRL(148)*, 2021, pp. 15-21.

Elsevier DOI
**2107**

Graph neural networks, Self-supervised learning,
Multi-task learning, Graph convolutional networks, Semi-supervised learning
BibRef

*Wang, W.[Wei]*,
*Gao, J.Y.[Jun-Yu]*,
*Yang, X.S.[Xiao-Shan]*,
*Xu, C.S.[Chang-Sheng]*,

**Learning Coarse-to-Fine Graph Neural Networks for Video-Text
Retrieval**,

*MultMed(23)*, 2021, pp. 2386-2397.

IEEE DOI
**2108**

Feature extraction, Encoding, Task analysis, Semantics, Data models,
Cognition, Focusing, Video-text retrieval, graph neural network,
coarse-to-fine strategy
BibRef

*Abadal, S.[Sergi]*,
*Jain, A.[Akshay]*,
*Guirado, R.[Robert]*,
*Lopez-Alonso, J.[Jorge]*,
*Alarcon, E.[Eduard]*,

**Computing Graph Neural Networks: A Survey from Algorithms to
Accelerators**,

*Surveys(54)*, No. 9, October 2021, pp. xx-yy.

DOI Link
**2112**

*Survey, Graph Neural Networks*. Graph neural networks, GNN algorithms, graph embeddings, accelerators
BibRef

*Tiezzi, M.[Matteo]*,
*Marra, G.[Giuseppe]*,
*Melacci, S.[Stefano]*,
*Maggini, M.[Marco]*,

**Deep Constraint-Based Propagation in Graph Neural Networks**,

*PAMI(44)*, No. 2, February 2022, pp. 727-739.

IEEE DOI
**2201**

Optimization, Computational modeling, Training,
Graph neural networks, Data models, Biological neural networks,
lagrangian optimization
BibRef

*Ciano, G.[Giorgio]*,
*Rossi, A.[Alberto]*,
*Bianchini, M.[Monica]*,
*Scarselli, F.[Franco]*,

**On Inductive-Transductive Learning With Graph Neural Networks**,

*PAMI(44)*, No. 2, February 2022, pp. 758-769.

IEEE DOI
**2201**

Neural networks, Computational modeling, Training, Encoding,
Graph neural networks, Topology, Diffusion processes,
inductive learning
BibRef

*Ding, J.Y.[Jing-Yi]*,
*Cheng, R.[Ruohui]*,
*Song, J.[Jian]*,
*Zhang, X.R.[Xiang-Rong]*,
*Jiao, L.C.[Li-Cheng]*,
*Wu, J.[Jianshe]*,

**Graph label prediction based on local structure characteristics
representation**,

*PR(125)*, 2022, pp. 108525.

Elsevier DOI
**2203**

Graph classification, Graph neural network,
Betweenness centrality node, Feature fusion, Characteristics representation
BibRef

*Chen, Y.C.[Yu-Chi]*,
*Lai, K.T.[Kuan-Ting]*,
*Liu, D.[Dong]*,
*Chen, M.S.[Ming-Syan]*,

**TAGNet: Triplet-Attention Graph Networks for Hashtag Recommendation**,

*CirSysVideo(32)*, No. 3, March 2022, pp. 1148-1159.

IEEE DOI
**2203**

Feature extraction, Visualization, Social networking (online),
Correlation, Convolution, Fuses, Blogs, Hashtag recommendation,
attention mechanism
BibRef

*Kan, S.C.[Shi-Chao]*,
*Cen, Y.G.[Yi-Gang]*,
*Li, Y.[Yang]*,
*Vladimir, M.[Mladenovic]*,
*He, Z.H.[Zhi-Hai]*,

**Local Semantic Correlation Modeling Over Graph Neural Networks for
Deep Feature Embedding and Image Retrieval**,

*IP(31)*, 2022, pp. 2988-3003.

IEEE DOI
**2205**

Correlation, Graph neural networks, Measurement, Semantics,
Image retrieval, Training, Visualization, Deep feature embedding
BibRef

*Thang, D.C.[Duong Chi]*,
*Dat, H.T.[Hoang Thanh]*,
*Tam, N.T.[Nguyen Thanh]*,
*Jo, J.[Jun]*,
*Hung, N.Q.V.[Nguyen Quoc Viet]*,
*Aberer, K.[Karl]*,

**Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks**,

*PRL(159)*, 2022, pp. 46-53.

Elsevier DOI
**2206**

graph neural networks, transferability
BibRef

*Gao, H.Y.[Hong-Yang]*,
*Ji, S.W.[Shui-Wang]*,

**Graph U-Nets**,

*PAMI(44)*, No. 9, September 2022, pp. 4948-4960.

IEEE DOI
**2208**

Task analysis, Topology, Feature extraction,
Neural networks, Logic gates, Lattices, Graph neural networks, U-Net
BibRef

*Wang, R.Z.[Run-Zhong]*,
*Yan, J.C.[Jun-Chi]*,
*Yang, X.K.[Xiao-Kang]*,

**Neural Graph Matching Network: Learning Lawler's Quadratic Assignment
Problem With Extension to Hypergraph and Multiple-Graph Matching**,

*PAMI(44)*, No. 9, September 2022, pp. 5261-5279.

IEEE DOI
**2208**

Pattern matching, Tensors, Splines (mathematics),
Feature extraction, Peer-to-peer computing, Optimization,
graph neural networks
BibRef

*Tian, Y.[Yu]*,
*Sun, X.[Xian]*,
*Niu, R.G.[Rui-Gang]*,
*Yu, H.F.[Hong-Feng]*,
*Zhu, Z.C.[Zi-Cong]*,
*Wang, P.[Peijin]*,
*Fu, K.[Kun]*,

**Fully-weighted HGNN: Learning efficient non-local relations with
hypergraph in aerial imagery**,

*PandRS(191)*, 2022, pp. 263-276.

Elsevier DOI
**2208**

Aerial imagery, Hypergraph neural networks,
Fully-weighted Hypergraph Neural Network (fully-weighted HGNN),
Hypergraph Convolutional Feature Pyramid Networks (hyper-FPN)
BibRef

*Isufi, E.[Elvin]*,
*Gama, F.[Fernando]*,
*Ribeiro, A.[Alejandro]*,

**EdgeNets: Edge Varying Graph Neural Networks**,

*PAMI(44)*, No. 11, November 2022, pp. 7457-7473.

IEEE DOI
**2210**

Convolution, Neural networks, Graph neural networks,
Computational complexity, Tools, Laplace equations, Edge varying,
learning on graphs
BibRef

*Liu, M.[Meng]*,
*Wang, Z.Y.[Zheng-Yang]*,
*Ji, S.W.[Shui-Wang]*,

**Non-Local Graph Neural Networks**,

*PAMI(44)*, No. 12, December 2022, pp. 10270-10276.

IEEE DOI
**2212**

Sorting, Task analysis, Graph neural networks, Convolution,
Aggregates, Nonhomogeneous media, Calibration, disassortative graphs
BibRef

*Li, S.[Shuo]*,
*Liu, F.[Fang]*,
*Jiao, L.C.[Li-Cheng]*,
*Chen, P.[Puhua]*,
*Liu, X.[Xu]*,
*Li, L.L.[Ling-Ling]*,

**MFNet: A Novel GNN-Based Multi-Level Feature Network With Superpixel
Priors**,

*IP(31)*, 2022, pp. 7306-7321.

IEEE DOI
**2212**

Feature extraction, Task analysis, Object detection,
Image segmentation, Convolution, Graph neural networks, Shape,
representation learning
BibRef

*Bouritsas, G.[Giorgos]*,
*Frasca, F.[Fabrizio]*,
*Zafeiriou, S.P.[Stefanos P.]*,
*Bronstein, M.M.[Michael M.]*,

**Improving Graph Neural Network Expressivity via Subgraph Isomorphism
Counting**,

*PAMI(45)*, No. 1, January 2023, pp. 657-668.

IEEE DOI
**2212**

Orbits, Message passing, Graph neural networks, Color,
Social networking (online), Proteins, Histograms, neural network expressivity
BibRef

*Abdelaziz, I.[Ibrahim]*,
*Crouse, M.[Maxwell]*,
*Makni, B.[Bassem]*,
*Austel, V.[Vernon]*,
*Cornelio, C.[Cristina]*,
*Ikbal, S.[Shajith]*,
*Kapanipathi, P.[Pavan]*,
*Makondo, N.[Ndivhuwo]*,
*Srinivas, K.[Kavitha]*,
*Witbrock, M.[Michael]*,
*Fokoue, A.[Achille]*,

**Learning to Guide a Saturation-Based Theorem Prover**,

*PAMI(45)*, No. 1, January 2023, pp. 738-751.

IEEE DOI
**2212**

Standards, Reinforcement learning, Graph neural networks,
Feature extraction, Benchmark testing, Search problems,
graph neural networks
BibRef

*Xie, Y.C.[Yao-Chen]*,
*Xu, Z.[Zhao]*,
*Zhang, J.T.[Jing-Tun]*,
*Wang, Z.Y.[Zheng-Yang]*,
*Ji, S.W.[Shui-Wang]*,

**Self-Supervised Learning of Graph Neural Networks: A Unified Review**,

*PAMI(45)*, No. 2, February 2023, pp. 2412-2429.

IEEE DOI
**2301**

Task analysis, Predictive models, Data models, Training,
Graph neural networks, Mutual information, Head, Deep learning,
unsupervised learning
BibRef

*Chen, T.L.[Tian-Long]*,
*Zhou, K.X.[Kai-Xiong]*,
*Duan, K.Y.[Ke-Yu]*,
*Zheng, W.Q.[Wen-Qing]*,
*Wang, P.H.[Pei-Hao]*,
*Hu, X.[Xia]*,
*Wang, Z.Y.[Zhang-Yang]*,

**Bag of Tricks for Training Deeper Graph Neural Networks:
A Comprehensive Benchmark Study**,

*PAMI(45)*, No. 3, March 2023, pp. 2769-2781.

IEEE DOI
**2302**

Training, Benchmark testing, Standards, Peer-to-peer computing,
Graph neural networks, Task analysis, Deep graph neural networks, benchmark
BibRef

*Vasudevan, V.[Varun]*,
*Bassenne, M.[Maxime]*,
*Islam, M.T.[Md Tauhidul]*,
*Xing, L.[Lei]*,

**Image classification using graph neural network and multiscale
wavelet superpixels**,

*PRL(166)*, 2023, pp. 89-96.

Elsevier DOI
**2302**

Image classification, GNN, Multiscale superpixel, Wavelet
BibRef

*Qian, S.S.[Sheng-Sheng]*,
*Xue, D.[Dizhan]*,
*Fang, Q.[Quan]*,
*Xu, C.S.[Chang-Sheng]*,

**Integrating Multi-Label Contrastive Learning With Dual Adversarial
Graph Neural Networks for Cross-Modal Retrieval**,

*PAMI(45)*, No. 4, April 2023, pp. 4794-4811.

IEEE DOI
**2303**

Semantics, Correlation, Data models, Task analysis,
Graph neural networks, Generative adversarial networks, Training
BibRef

*Mohamed, H.A.[Hebatallah A.]*,
*Pilutti, D.[Diego]*,
*James, S.[Stuart]*,
*del Bue, A.[Alessio]*,
*Pelillo, M.[Marcello]*,
*Vascon, S.[Sebastiano]*,

**Locality-aware subgraphs for inductive link prediction in knowledge
graphs**,

*PRL(167)*, 2023, pp. 90-97.

Elsevier DOI
**2303**

Knowledge graphs, Inductive link prediction,
Graph neural networks, Local clustering, Personalized PageRank
BibRef

*Kaczmarek, I.[Iwona]*,
*Iwaniak, A.[Adam]*,
*Swietlicka, A.[Aleksandra]*,

**Classification of Spatial Objects with the Use of Graph Neural
Networks**,

*IJGI(12)*, No. 3, 2023, pp. xx-yy.

DOI Link
**2303**

BibRef

*Fan, X.L.[Xiao-Long]*,
*Gong, M.[Maoguo]*,
*Wu, Y.[Yue]*,

**Markov clustering regularized multi-hop graph neural network**,

*PR(139)*, 2023, pp. 109518.

Elsevier DOI
**2304**

Graph data mining, Graph neural network,
Graph-level representation learning, Graph pattern recognition
BibRef

*Hao, Y.J.[Yong-Jing]*,
*Ma, J.[Jun]*,
*Zhao, P.P.[Peng-Peng]*,
*Liu, G.F.[Guan-Feng]*,
*Xian, X.F.[Xue-Feng]*,
*Zhao, L.[Lei]*,
*Sheng, V.S.[Victor S.]*,

**Multi-dimensional Graph Neural Network for Sequential Recommendation**,

*PR(139)*, 2023, pp. 109504.

Elsevier DOI
**2304**

Sequential Recommendation, Graph Neural Networks,
Self-attention Networks, Graph Embedding
BibRef

*Wang, Z.Y.[Zheng-Yang]*,
*Ji, S.W.[Shui-Wang]*,

**Second-Order Pooling for Graph Neural Networks**,

*PAMI(45)*, No. 6, June 2023, pp. 6870-6880.

IEEE DOI
**2305**

Neural networks, Task analysis, Deep learning, Correlation, Covariance matrices,
Graph neural networks, graph pooling, second-order statistics
BibRef

*Mueller, T.T.[Tamara T.]*,
*Paetzold, J.C.[Johannes C.]*,
*Prabhakar, C.[Chinmay]*,
*Usynin, D.[Dmitrii]*,
*Rueckert, D.[Daniel]*,
*Kaissis, G.[Georgios]*,

**Differentially Private Graph Neural Networks for Whole-Graph
Classification**,

*PAMI(45)*, No. 6, June 2023, pp. 7308-7318.

IEEE DOI
**2305**

Training, Privacy, Task analysis, Graph neural networks, Data models,
Stochastic processes, Image edge detection, Differential privacy,
graph neural networks
BibRef

*Jiang, X.D.[Xiao-Dong]*,
*Zhu, R.H.[Rong-Hang]*,
*Ji, P.S.[Peng-Sheng]*,
*Li, S.[Sheng]*,

**Co-Embedding of Nodes and Edges With Graph Neural Networks**,

*PAMI(45)*, No. 6, June 2023, pp. 7075-7086.

IEEE DOI
**2305**

Task analysis, Convolution, Deep learning, Switches,
Image edge detection, Prediction algorithms, Graph embedding, link prediction
BibRef

*Wan, H.[Hai]*,
*Zhang, X.W.[Xin-Wei]*,
*Zhang, Y.[Yubo]*,
*Zhao, X.[Xibin]*,
*Ying, S.[Shihui]*,
*Gao, Y.[Yue]*,

**Structure Evolution on Manifold for Graph Learning**,

*PAMI(45)*, No. 6, June 2023, pp. 7751-7763.

IEEE DOI
**2305**

Manifolds, Task analysis, Convolution, Data models,
Graph neural networks, Energy measurement, Correlation, graph energy
BibRef

*Lyu, S.[Shuaiyi]*,
*Wang, K.[Kai]*,
*Zhang, L.[Liren]*,
*Wang, B.L.[Bai-Ling]*,

**Process-Oriented heterogeneous graph learning in GNN-Based ICS
anomalous pattern recognition**,

*PR(141)*, 2023, pp. 109661.

Elsevier DOI
**2306**

Fine-Grained anomaly recognition, Process-Oriented associativity,
Heterogeneous graph learning, Industrial control systems
BibRef

Springer DOI

BibRef

*Gillioz, A.[Anthony]*,
*Riesen, K.[Kaspar]*,

**Graph Reduction Neural Networks for Structural Pattern Recognition**,

*SSSPR22*(64-73).

Springer DOI
**2301**

BibRef

*Seo, S.[Sangwoo]*,
*Jung, S.[Seungjun]*,
*Kim, C.[Changick]*,

**Explanation-based Graph Neural Networks for Graph Classification**,

*ICPR22*(2836-2842)

IEEE DOI
**2212**

Proteins, Analytical models, Machine learning,
Benchmark testing, Graph neural networks, Data models
BibRef

*Wei, Z.[Ziyu]*,
*Xiao, X.[Xi]*,
*Zhang, B.[Bin]*,
*Hu, G.W.[Guang-Wu]*,
*Li, Q.[Qing]*,
*Xia, S.T.[Shu-Tao]*,

**Graph Data Augmentation for Node Classification**,

*ICPR22*(4899-4905)

IEEE DOI
**2212**

Computational modeling, Benchmark testing, Graph neural networks, Topology
BibRef

*Kim, J.[Jinwoo]*,
*Oh, S.[Saeyoon]*,
*Cho, S.J.[Sung-Jun]*,
*Hong, S.[Seunghoon]*,

**Equivariant Hypergraph Neural Networks**,

*ECCV22*(XXI:86-103).

Springer DOI
**2211**

BibRef

*Lin, W.[Wanyu]*,
*Lan, H.[Hao]*,
*Wang, H.[Hao]*,
*Li, B.[Baochun]*,

**OrphicX: A Causality-Inspired Latent Variable Model for Interpreting
Graph Neural Networks**,

*CVPR22*(13719-13728)

IEEE DOI
**2210**

Visualization, Privacy, Statistical analysis, Semantics,
Training data, Medical services, privacy and ethics in vision, Transparency
BibRef

*Schaefer, S.[Simon]*,
*Gehrig, D.[Daniel]*,
*Scaramuzza, D.[Davide]*,

**AEGNN: Asynchronous Event-based Graph Neural Networks**,

*CVPR22*(12361-12371)

IEEE DOI
**2210**

*Code, GNN*.

WWW Link. Power demand, Object detection, Market research,
Graph neural networks, Pattern recognition, Object recognition,
Scene analysis and understanding
BibRef

*Wu, H.Y.[Hong-Yan]*,
*Guo, H.Y.[Hai-Yun]*,
*Miao, Q.H.[Qing-Hai]*,
*Huang, M.[Min]*,
*Wang, J.Q.[Jin-Qiao]*,

**Graph Neural Networks Based Multi-granularity Feature Representation
Learning for Fine-Grained Visual Categorization**,

*MMMod22*(II:230-242).

Springer DOI
**2203**

BibRef

*Zhao, G.M.[Gang-Ming]*,
*Ge, W.F.[Wei-Feng]*,
*Yu, Y.Z.[Yi-Zhou]*,

**GraphFPN: Graph Feature Pyramid Network for Object Detection**,

*ICCV21*(2743-2752)

IEEE DOI
**2203**

Representation learning, Image segmentation, Network topology,
Object detection, Feature extraction, Graph neural networks,
grouping and shape
BibRef

*Xing, Y.F.[Yi-Fan]*,
*He, T.[Tong]*,
*Xiao, T.J.[Tian-Jun]*,
*Wang, Y.X.[Yong-Xin]*,
*Xiong, Y.J.[Yuan-Jun]*,
*Xia, W.[Wei]*,
*Wipf, D.[David]*,
*Zhang, Z.[Zheng]*,
*Soatto, S.[Stefano]*,

**Learning Hierarchical Graph Neural Networks for Image Clustering**,

*ICCV21*(3447-3457)

IEEE DOI
**2203**

Training, Couplings, Computational modeling, Predictive models,
Prediction algorithms, Graph neural networks, Faces,
Recognition and classification
BibRef

*Liu, N.[Nian]*,
*Zhao, W.[Wangbo]*,
*Zhang, D.W.[Ding-Wen]*,
*Han, J.W.[Jun-Wei]*,
*Shao, L.[Ling]*,

**Light Field Saliency Detection with Dual Local Graph Learning and
Reciprocative Guidance**,

*ICCV21*(4692-4701)

IEEE DOI
**2203**

Fuses, Convolution, Computational modeling, Object detection,
Light fields, Graph neural networks,
Scene analysis and understanding
BibRef

*Wang, T.T.[Tian-Tian]*,
*Liu, S.[Sifei]*,
*Tian, Y.[Yapeng]*,
*Li, K.[Kai]*,
*Yang, M.H.[Ming-Hsuan]*,

**Video Matting via Consistency-Regularized Graph Neural Networks**,

*ICCV21*(4882-4891)

IEEE DOI
**2203**

Training, Adaptation models, Computational modeling, Coherence,
Predictive models, Graph neural networks,
grouping and shape
BibRef

*Jing, Y.C.[Yong-Cheng]*,
*Yang, Y.D.[Yi-Ding]*,
*Wang, X.C.[Xin-Chao]*,
*Song, M.L.[Ming-Li]*,
*Tao, D.C.[Da-Cheng]*,

**Meta-Aggregator: Learning to Aggregate for 1-bit Graph Neural
Networks**,

*ICCV21*(5281-5290)

IEEE DOI
**2203**

Visualization, Adaptation models, Network topology,
Computational modeling, Aggregates, Transformers,
Vision applications and systems
BibRef

*Li, X.Y.[Xin-Yi]*,
*Ling, H.B.[Hai-Bin]*,

**PoGO-Net: Pose Graph Optimization with Graph Neural Networks**,

*ICCV21*(5875-5885)

IEEE DOI
**2203**

Training, Simultaneous localization and mapping, Pose estimation,
Benchmark testing, Cameras, Robustness, Graph neural networks,
Vision for robotics and autonomous vehicles
BibRef

*Chen, H.K.[Hong-Kai]*,
*Luo, Z.X.[Zi-Xin]*,
*Zhang, J.H.[Jia-Hui]*,
*Zhou, L.[Lei]*,
*Bai, X.Y.[Xu-Yang]*,
*Hu, Z.[Zeyu]*,
*Tai, C.L.[Chiew-Lan]*,
*Quan, L.[Long]*,

**Learning to Match Features with Seeded Graph Matching Network**,

*ICCV21*(6281-6290)

IEEE DOI
**2203**

Costs, Filtering, Message passing, Image matching,
Computer network reliability, Graph neural networks, Stereo,
Low-level and physics-based vision
BibRef

*Arnab, A.[Anurag]*,
*Sun, C.[Chen]*,
*Schmid, C.[Cordelia]*,

**Unified Graph Structured Models for Video Understanding**,

*ICCV21*(8097-8106)

IEEE DOI
**2203**

Computational modeling, Message passing, Genomics, Cognition,
Graph neural networks, Task analysis,
Action and behavior recognition
BibRef

*Fang, P.F.[Peng-Fei]*,
*Harandi, M.[Mehrtash]*,
*Petersson, L.[Lars]*,

**Kernel Methods in Hyperbolic Spaces**,

*ICCV21*(10645-10654)

IEEE DOI
**2203**

Geometry, Machine learning, Hilbert space,
Natural language processing, Graph neural networks,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef

*Zeng, A.[Ailing]*,
*Sun, X.[Xiao]*,
*Yang, L.[Lei]*,
*Zhao, N.X.[Nan-Xuan]*,
*Liu, M.H.[Min-Hao]*,
*Xu, Q.[Qiang]*,

**Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation**,

*ICCV21*(11416-11425)

IEEE DOI
**2203**

Representation learning, Deep learning, Codes, Pose estimation,
Graph neural networks, Gestures and body pose,
Representation learning
BibRef

*Zhang, C.[Cheng]*,
*Cui, Z.P.[Zhao-Peng]*,
*Chen, C.[Cai]*,
*Liu, S.C.[Shuai-Cheng]*,
*Zeng, B.[Bing]*,
*Bao, H.J.[Hu-Jun]*,
*Zhang, Y.[Yinda]*,

**DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene
Context Graph and Relation-based Optimization**,

*ICCV21*(12612-12621)

IEEE DOI
**2203**

Shape, Layout, Semantics, Predictive models, Linear programming,
Graph neural networks, 3D from a single image and shape-from-x,
Detection and localization in 2D and 3D
BibRef

*Yew, Z.J.[Zi Jian]*,
*Lee, G.H.[Gim Hee]*,

**Learning Iterative Robust Transformation Synchronization**,

*3DV21*(1206-1215)

IEEE DOI
**2201**

Analytical models, Message passing, Pipelines,
Graph neural networks, Synchronization, Iterative methods, registration
BibRef

*Bahri, M.[Mehdi]*,
*Bahl, G.[Gaétan]*,
*Zafeiriou, S.P.[Stefanos P.]*,

**Binary Graph Neural Networks**,

*CVPR21*(9487-9496)

IEEE DOI
**2111**

Training, Schedules, Heuristic algorithms, Computational modeling,
Memory management, Process control, Benchmark testing
BibRef

*Miyata, M.[Masaki]*,
*Shiraki, K.[Katsutoshi]*,
*Minoura, H.[Hiroaki]*,
*Hirakawa, T.[Tsubasa]*,
*Yamashita, T.[Takayoshi]*,
*Fujiyoshi, H.[Hironobu]*,

**Relational Subgraph for Graph-based Path Prediction**,

*MVA21*(1-5)

DOI Link
**2109**

Prediction methods, Feature extraction
BibRef

*Dominguez, M.[Miguel]*,
*Ptucha, R.[Raymond]*,

**Directional Graph Networks with Hard Weight Assignments**,

*ICPR21*(7439-7446)

IEEE DOI
**2105**

Convolution, Computational modeling,
Neural networks, Robot sensing systems, Computational efficiency, Sensors
BibRef

*Tian, Y.X.[Yu-Xing]*,
*Liu, Z.[Zheng]*,
*Liu, W.[Weiding]*,
*Zhang, Z.[Zeyu]*,
*Qu, Y.[Yanwen]*,

**What nodes vote to? Graph classification without readout phase**,

*ICPR21*(8439-8445)

IEEE DOI
**2105**

Message passing, Logic gates, Benchmark testing,
Feature extraction, Graph neural networks, Decoding,
graph neural networks
BibRef

*Park, H.*,
*Jeong, M.*,
*Kim, Y.*,
*Kim, C.*,

**Self-Training Of Graph Neural Networks Using Similarity Reference For
Robust Training With Noisy Labels**,

*ICIP20*(1951-1955)

IEEE DOI
**2011**

Training, Sampling methods, Noise measurement, Feature extraction,
Training data, Indexes, Data mining, Noisy label, sampling method,
graph-based CNN.
BibRef

*Yu, C.Q.[Chang-Qian]*,
*Liu, Y.F.[Yi-Fan]*,
*Gao, C.X.[Chang-Xin]*,
*Shen, C.H.[Chun-Hua]*,
*Sang, N.[Nong]*,

**Representative Graph Neural Network**,

*ECCV20*(VII:379-396).

Springer DOI
**2011**

BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in

Graph Convolutional Neural Networks .

Last update:Jun 1, 2023 at 10:05:03