{"list":"other","total":62,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","created":"2016-09-09","cited_by_count":11361},{"id":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"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":"1810.00826","title":"How Powerful are Graph Neural Networks?","created":"2018-10-01","cited_by_count":4393},{"id":"1704.01212","title":"Neural Message Passing for Quantum Chemistry","created":"2017-04-04","cited_by_count":3487},{"id":"1901.00596","title":"A Comprehensive Survey on Graph Neural Networks","created":"2019-01-03","cited_by_count":2919},{"id":"1611.01144","title":"Categorical Reparameterization with Gumbel-Softmax","created":"2016-11-03","cited_by_count":2739},{"id":"1903.02428","title":"Fast Graph Representation Learning with PyTorch Geometric","created":"2019-03-06","cited_by_count":2434},{"id":"2005.00687","title":"Open Graph Benchmark: Datasets for Machine Learning on Graphs","created":"2020-05-02","cited_by_count":2163},{"id":"1606.09375","title":"Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering","created":"2016-06-30","cited_by_count":2089},{"id":"1812.08434","title":"Graph Neural Networks: A Review of Methods and Applications","created":"2018-12-20","cited_by_count":1576},{"id":"1611.07308","title":"Variational Graph Auto-Encoders","created":"2016-11-21","cited_by_count":1382},{"id":"1902.02918","title":"Certified Adversarial Robustness via Randomized Smoothing","created":"2019-02-08","cited_by_count":1340},{"id":"1611.00712","title":"The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables","created":"2016-11-02","cited_by_count":1148},{"id":"1806.01973","title":"Graph Convolutional Neural Networks for Web-Scale Recommender Systems","created":"2018-06-06","cited_by_count":1138},{"id":"1809.10341","title":"Deep Graph Infomax","created":"2018-09-27","cited_by_count":1106},{"id":"1312.6203","title":"Spectral Networks and Locally Connected Networks on Graphs","created":"2013-12-21","cited_by_count":1102},{"id":"1801.07606","title":"Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning","created":"2018-01-22","cited_by_count":1102},{"id":"1703.00564","title":"MoleculeNet: A Benchmark for Molecular Machine Learning","created":"2017-03-02","cited_by_count":1051},{"id":"1810.05997","title":"Predict then Propagate: Graph Neural Networks meet Personalized PageRank","created":"2018-10-14","cited_by_count":993},{"id":"1806.03536","title":"Representation Learning on Graphs with Jumping Knowledge Networks","created":"2018-06-09","cited_by_count":877},{"id":"2007.02133","title":"Simple and Deep Graph Convolutional Networks","created":"2020-07-04","cited_by_count":860},{"id":"2105.14491","title":"How Attentive are Graph Attention Networks?","created":"2021-05-30","cited_by_count":835},{"id":"2002.05287","title":"Geom-GCN: Geometric Graph Convolutional Networks","created":"2020-02-13","cited_by_count":826},{"id":"1511.05493","title":"Gated Graph Sequence Neural Networks","created":"2015-11-17","cited_by_count":796},{"id":"1907.10903","title":"DropEdge: Towards Deep Graph Convolutional Networks on Node Classification","created":"2019-07-25","cited_by_count":680},{"id":"1907.04931","title":"GraphSAINT: Graph Sampling Based Inductive Learning Method","created":"2019-07-10","cited_by_count":618},{"id":"1801.10247","title":"FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling","created":"2018-01-30","cited_by_count":584},{"id":"1809.06839","title":"Albumentations: fast and flexible image augmentations","created":"2018-09-18","cited_by_count":560},{"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":"1805.07984","title":"Adversarial Attacks on Neural Networks for Graph Data","created":"2018-05-21","cited_by_count":397},{"id":"2005.10203","title":"Graph Structure Learning for Robust Graph Neural Networks","created":"2020-05-20","cited_by_count":371},{"id":"2101.00797","title":"Beyond Low-frequency Information in Graph Convolutional Networks","created":"2021-01-04","cited_by_count":362},{"id":"1909.12223","title":"PairNorm: Tackling Oversmoothing in GNNs","created":"2019-09-26","cited_by_count":297},{"id":"2007.09296","title":"Towards Deeper Graph Neural Networks","created":"2020-07-18","cited_by_count":296},{"id":"1511.02136","title":"Diffusion-Convolutional Neural Networks","created":"2015-11-06","cited_by_count":268},{"id":"1803.01229","title":"GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification","created":"2018-03-03","cited_by_count":242},{"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":"1906.04214","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","created":"2019-06-10","cited_by_count":196},{"id":"2010.12811","title":"Graph Information Bottleneck","created":"2020-10-24","cited_by_count":168},{"id":"2110.07580","title":"Graph Condensation for Graph Neural Networks","created":"2021-10-14","cited_by_count":150},{"id":"2202.08235","title":"Data Augmentation for Deep Graph Learning: A Survey","created":"2022-02-16","cited_by_count":133},{"id":"2011.07057","title":"Learning to Drop: Robust Graph Neural Network via Topological Denoising","created":"2020-11-13","cited_by_count":127},{"id":"2111.06283","title":"DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks","created":"2021-11-11","cited_by_count":118},{"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":"1307.1493","title":"Dropout Training as Adaptive Regularization","created":"2013-07-04","cited_by_count":93},{"id":"2005.06149","title":"DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses","created":"2020-05-13","cited_by_count":78},{"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":"2102.01350","title":"Graph Coarsening with Neural Networks","created":"2021-02-02","cited_by_count":55},{"id":"1905.01591","title":"Learning Graph Neural Networks with Noisy Labels","created":"2019-05-05","cited_by_count":30},{"id":"1811.07609","title":"Outlier Aware Network Embedding for Attributed Networks","created":"2018-11-19","cited_by_count":29},{"id":"2112.09810","title":"Meta Propagation Networks for Graph Few-shot Semi-supervised Learning","created":"2021-12-18","cited_by_count":25},{"id":"1809.00130","title":"Semi-supervised Learning on Graphs with Generative Adversarial Nets","created":"2018-09-01","cited_by_count":21},{"id":"1905.10947","title":"Graph Neural Networks Exponentially Lose Expressive Power for Node Classification","created":"2019-05-27","cited_by_count":16},{"id":"1805.03327","title":"Network Enhancement: a general method to denoise weighted biological networks","created":"2018-05-09","cited_by_count":15},{"id":"1703.08100","title":"Semi-supervised Embedding in Attributed Networks with Outliers","created":"2017-03-23","cited_by_count":10},{"id":"2202.12508","title":"Addressing Over-Smoothing in Graph Neural Networks via Deep Supervision","created":"2022-02-25","cited_by_count":7},{"id":"1408.0845","title":"Predicting missing links and their weights via reliable-route-based method","created":"2014-08-05","cited_by_count":3},{"id":"1902.08440","title":"Robust Graph Embedding with Noisy Link Weights","created":"2019-02-22","cited_by_count":3}],"next_cursor":null}