{"list":"other","total":79,"rows":[{"id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","created":"2016-09-09","cited_by_count":11361},{"id":"1706.02216","title":"Inductive Representation Learning on Large Graphs","created":"2017-06-07","cited_by_count":6320},{"id":"1710.09412","title":"mixup: Beyond Empirical Risk Minimization","created":"2017-10-25","cited_by_count":5183},{"id":"1905.04899","title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","created":"2019-05-13","cited_by_count":2884},{"id":"1607.00653","title":"node2vec: Scalable Feature Learning for Networks","created":"2016-07-03","cited_by_count":1918},{"id":"1911.04252","title":"Self-training with Noisy Student improves ImageNet classification","created":"2019-11-11","cited_by_count":1311},{"id":"2010.13902","title":"Graph Contrastive Learning with Augmentations","created":"2020-10-22","cited_by_count":1208},{"id":"1809.10341","title":"Deep Graph Infomax","created":"2018-09-27","cited_by_count":1106},{"id":"1801.07606","title":"Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning","created":"2018-01-22","cited_by_count":1102},{"id":"1905.12265","title":"Strategies for Pre-training Graph Neural Networks","created":"2019-05-29","cited_by_count":971},{"id":"1907.10903","title":"DropEdge: Towards Deep Graph Convolutional Networks on Node Classification","created":"2019-07-25","cited_by_count":680},{"id":"2006.05582","title":"Contrastive Multi-View Representation Learning on Graphs","created":"2020-06-10","cited_by_count":652},{"id":"1909.03211","title":"Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View","created":"2019-09-07","cited_by_count":545},{"id":"2006.04131","title":"Deep Graph Contrastive Representation Learning","created":"2020-06-07","cited_by_count":539},{"id":"1904.03751","title":"DeepGCNs: Can GCNs Go as Deep as CNNs?","created":"2019-04-07","cited_by_count":527},{"id":"2010.14945","title":"Graph Contrastive Learning with Adaptive Augmentation","created":"2020-10-27","cited_by_count":519},{"id":"2006.09963","title":"GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training","created":"2020-06-17","cited_by_count":463},{"id":"1908.01000","title":"InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization","created":"2019-07-31","cited_by_count":441},{"id":"1911.05485","title":"Diffusion Improves Graph Learning","created":"2019-10-28","cited_by_count":414},{"id":"2105.03075","title":"A Survey of Data Augmentation Approaches for NLP","created":"2021-05-07","cited_by_count":409},{"id":"2010.10783","title":"Self-supervised Graph Learning for Recommendation","created":"2020-10-21","cited_by_count":305},{"id":"2103.00111","title":"Graph Self-Supervised Learning: A Survey","created":"2021-02-27","cited_by_count":289},{"id":"2106.07594","title":"Graph Contrastive Learning Automated","created":"2021-06-10","cited_by_count":287},{"id":"2005.11079","title":"Graph Random Neural Network for Semi-Supervised Learning on Graphs","created":"2020-05-22","cited_by_count":213},{"id":"2006.06830","title":"Data Augmentation for Graph Neural Networks","created":"2020-06-11","cited_by_count":203},{"id":"2106.05819","title":"Adversarial Graph Augmentation to Improve Graph Contrastive Learning","created":"2021-06-10","cited_by_count":200},{"id":"2010.04819","title":"How Does Mixup Help With Robustness and Generalization?","created":"2020-10-09","cited_by_count":193},{"id":"2102.06514","title":"Large-Scale Representation Learning on Graphs via Bootstrapping","created":"2021-02-12","cited_by_count":186},{"id":"2102.10757","title":"Self-Supervised Learning of Graph Neural Networks: A Unified Review","created":"2021-02-22","cited_by_count":184},{"id":"2103.08826","title":"GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks","created":"2021-03-16","cited_by_count":147},{"id":"2202.07179","title":"G-Mixup: Graph Data Augmentation for Graph Classification","created":"2022-02-15","cited_by_count":146},{"id":"2106.12484","title":"From Canonical Correlation Analysis to Self-supervised Graph Neural Networks","created":"2021-06-23","cited_by_count":141},{"id":"2105.07342","title":"Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive","created":"2021-05-16","cited_by_count":136},{"id":"2202.08235","title":"Data Augmentation for Deep Graph Learning: A Survey","created":"2022-02-16","cited_by_count":133},{"id":"2105.09111","title":"Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning","created":"2021-05-19","cited_by_count":130},{"id":"2011.07057","title":"Learning to Drop: Robust Graph Neural Network via Topological Denoising","created":"2020-11-13","cited_by_count":127},{"id":"2109.01116","title":"An Empirical Study of Graph Contrastive Learning","created":"2021-09-02","cited_by_count":113},{"id":"1902.11038","title":"Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels","created":"2019-02-28","cited_by_count":111},{"id":"2009.05204","title":"Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization","created":"2020-09-11","cited_by_count":93},{"id":"2009.10273","title":"Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning","created":"2020-09-22","cited_by_count":90},{"id":"2106.02466","title":"Graph Barlow Twins: A self-supervised representation learning framework for graphs","created":"2021-06-04","cited_by_count":85},{"id":"2102.07810","title":"HDMI: High-order Deep Multiplex Infomax","created":"2021-02-15","cited_by_count":82},{"id":"2212.04475","title":"Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction","created":"2022-12-07","cited_by_count":77},{"id":"2101.08170","title":"SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism","created":"2021-01-20","cited_by_count":75},{"id":"2106.04714","title":"NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs","created":"2021-06-08","cited_by_count":73},{"id":"2105.05682","title":"Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning","created":"2021-05-12","cited_by_count":70},{"id":"2206.02886","title":"Graph Rationalization with Environment-based Augmentations","created":"2022-06-06","cited_by_count":70},{"id":"2009.05923","title":"Contrastive Self-supervised Learning for Graph Classification","created":"2020-09-13","cited_by_count":68},{"id":"2104.14210","title":"FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning","created":"2021-04-29","cited_by_count":68},{"id":"2106.04509","title":"MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph","created":"2021-06-05","cited_by_count":65},{"id":"2204.12200","title":"Hypergraph Contrastive Collaborative Filtering","created":"2022-04-26","cited_by_count":63},{"id":"2202.08871","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","created":"2022-02-17","cited_by_count":62},{"id":"1706.07845","title":"HARP: Hierarchical Representation Learning for Networks","created":"2017-06-23","cited_by_count":58},{"id":"2010.09891","title":"Robust Optimization as Data Augmentation for Large-scale Graphs","created":"2020-10-19","cited_by_count":58},{"id":"1911.08538","title":"Heterogeneous Deep Graph Infomax","created":"2019-11-19","cited_by_count":42},{"id":"2108.11873","title":"When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?","created":"2021-08-26","cited_by_count":36},{"id":"2207.00012","title":"Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN","created":"2022-06-30","cited_by_count":34},{"id":"2109.04200","title":"Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation","created":"2021-09-09","cited_by_count":32},{"id":"2009.10564","title":"GraphCrop: Subgraph Cropping for Graph Classification","created":"2020-09-22","cited_by_count":31},{"id":"2111.05639","title":"Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation","created":"2021-11-10","cited_by_count":30},{"id":"2203.14082","title":"Metropolis-Hastings Data Augmentation for Graph Neural Networks","created":"2022-03-26","cited_by_count":30},{"id":"2210.03801","title":"Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative","created":"2022-10-07","cited_by_count":29},{"id":"1802.09612","title":"MILE: A Multi-Level Framework for Scalable Graph Embedding","created":"2018-02-26","cited_by_count":28},{"id":"2103.14958","title":"Self-supervised Graph Neural Networks without explicit negative sampling","created":"2021-03-27","cited_by_count":25},{"id":"2111.03220","title":"Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices","created":"2021-11-05","cited_by_count":25},{"id":"2009.09863","title":"Data Augmentation for Graph Classification","created":"2020-09-18","cited_by_count":22},{"id":"1904.06316","title":"Spatio-Temporal Deep Graph Infomax","created":"2019-04-12","cited_by_count":21},{"id":"2202.10107","title":"Model-Agnostic Augmentation for Accurate Graph Classification","created":"2022-02-21","cited_by_count":21},{"id":"2206.04739","title":"I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs","created":"2022-06-09","cited_by_count":21},{"id":"2203.09360","title":"Behavior-aware Account De-anonymization on Ethereum Interaction Graph","created":"2022-03-17","cited_by_count":17},{"id":"2102.13085","title":"Towards Robust Graph Contrastive Learning","created":"2021-02-25","cited_by_count":16},{"id":"2201.09830","title":"Learning Graph Augmentations to Learn Graph Representations","created":"2022-01-24","cited_by_count":14},{"id":"2007.05700","title":"M-Evolve: Structural-Mapping-Based Data Augmentation for Graph Classification","created":"2020-07-11","cited_by_count":11},{"id":"2203.09020","title":"Graph Augmentation Learning","created":"2022-03-17","cited_by_count":9},{"id":"1911.01670","title":"RobustECD: Enhancement of Network Structure for Robust Community Detection","created":"2019-11-05","cited_by_count":7},{"id":"2110.09344","title":"ifMixup: Interpolating Graph Pair to Regularize Graph Classification","created":"2021-10-18","cited_by_count":7},{"id":"2206.07895","title":"Dual-channel Early Warning Framework for Ethereum Ponzi Schemes","created":"2022-06-16","cited_by_count":6},{"id":"2103.13125","title":"Learning Graph Representation by Aggregating Subgraphs via Mutual Information Maximization","created":"2021-03-24","cited_by_count":5},{"id":"2208.11973","title":"Data Augmentation for Graph Data: Recent Advancements","created":"2022-08-25","cited_by_count":1}],"next_cursor":null}