{"list":"other","total":58,"rows":[{"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":"1810.00826","title":"How Powerful are Graph Neural Networks?","created":"2018-10-01","cited_by_count":4393},{"id":"2012.09699","title":"A Generalization of Transformer Networks to Graphs","created":"2020-12-17","cited_by_count":661},{"id":"2006.10637","title":"Temporal Graph Networks for Deep Learning on Dynamic Graphs","created":"2020-06-18","cited_by_count":530},{"id":"1908.01207","title":"Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks","created":"2019-08-03","cited_by_count":448},{"id":"1904.08082","title":"Self-Attention Graph Pooling","created":"2019-04-17","cited_by_count":421},{"id":"2102.04906","title":"Dynamic Neural Networks: A Survey","created":"2021-02-09","cited_by_count":408},{"id":"2110.07875","title":"Graph Neural Networks with Learnable Structural and Positional Representations","created":"2021-10-15","cited_by_count":333},{"id":"2103.00111","title":"Graph Self-Supervised Learning: A Survey","created":"2021-02-27","cited_by_count":289},{"id":"1612.07659","title":"Structured Sequence Modeling with Graph Convolutional Recurrent Networks","created":"2016-12-22","cited_by_count":275},{"id":"1702.07007","title":"Detecting causal associations in large nonlinear time series datasets","created":"2017-02-22","cited_by_count":244},{"id":"1802.03903","title":"Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications","created":"2018-02-12","cited_by_count":224},{"id":"1904.12787","title":"Graph Matching Networks for Learning the Similarity of Graph Structured Objects","created":"2019-04-29","cited_by_count":205},{"id":"1906.04817","title":"Position-aware Graph Neural Networks","created":"2019-06-11","cited_by_count":203},{"id":"1903.11835","title":"A Survey on Graph Kernels","created":"2019-03-28","cited_by_count":148},{"id":"2005.07496","title":"Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey","created":"2020-05-13","cited_by_count":124},{"id":"1704.06199","title":"Dynamic Graph Convolutional Networks","created":"2017-04-20","cited_by_count":83},{"id":"1906.10958","title":"Signed Graph Attention Networks","created":"2019-06-26","cited_by_count":62},{"id":"1904.12189","title":"Learning metrics for persistence-based summaries and applications for graph classification","created":"2019-04-27","cited_by_count":57},{"id":"2104.07368","title":"Dynamic Graph Neural Networks for Sequential Recommendation","created":"2021-04-15","cited_by_count":57},{"id":"2005.07427","title":"Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs","created":"2020-05-15","cited_by_count":56},{"id":"1806.02193","title":"GraKeL: A Graph Kernel Library in Python","created":"2018-06-06","cited_by_count":54},{"id":"2103.15447","title":"Dynamic Network Embedding Survey","created":"2021-03-29","cited_by_count":44},{"id":"2107.07702","title":"Neural Contextual Anomaly Detection for Time Series","created":"2021-07-16","cited_by_count":43},{"id":"1703.02161","title":"Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks","created":"2017-03-07","cited_by_count":40},{"id":"2007.04395","title":"Multilevel Graph Matching Networks for Deep Graph Similarity Learning","created":"2020-07-08","cited_by_count":29},{"id":"2007.01229","title":"Laplacian Change Point Detection for Dynamic Graphs","created":"2020-07-02","cited_by_count":25},{"id":"1606.06246","title":"High-dimensional changepoint estimation via sparse projection","created":"2016-06-20","cited_by_count":20},{"id":"1912.11615","title":"Deep Graph Similarity Learning: A Survey","created":"2019-12-25","cited_by_count":19},{"id":"2003.03668","title":"High-dimensional, multiscale online changepoint detection","created":"2020-03-07","cited_by_count":19},{"id":"1705.08415","title":"Supervised Community Detection with Line Graph Neural Networks","created":"2017-05-23","cited_by_count":18},{"id":"1403.0989","title":"Detecting change points in the large-scale structure of evolving networks","created":"2014-03-05","cited_by_count":13},{"id":"1707.00833","title":"Two-sample Hypothesis Testing for Inhomogeneous Random Graphs","created":"2017-07-04","cited_by_count":13},{"id":"1705.07325","title":"Fast Change Point Detection on Dynamic Social Networks","created":"2017-05-20","cited_by_count":11},{"id":"2201.08283","title":"Lead-lag detection and network clustering for multivariate time series with an application to the US equity market","created":"2022-01-20","cited_by_count":11},{"id":"2203.06601","title":"Dynamics on higher-order networks: A review","created":"2022-03-13","cited_by_count":11},{"id":"1808.06354","title":"Signed Graph Convolutional Network","created":"2018-08-20","cited_by_count":10},{"id":"1812.03090","title":"Change Point Estimation in a Dynamic Stochastic Block Model","created":"2018-12-07","cited_by_count":10},{"id":"1809.09602","title":"Optimal Change Point Detection and Localization in Sparse Dynamic Networks","created":"2018-09-25","cited_by_count":9},{"id":"1911.03583","title":"Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks","created":"2019-11-08","cited_by_count":9},{"id":"1707.03186","title":"Community Discovery in Dynamic Networks: a Survey","created":"2017-07-11","cited_by_count":8},{"id":"1410.0761","title":"Change Point Detection in Correlation Networks","created":"2014-10-03","cited_by_count":6},{"id":"2002.00727","title":"Distance Metric Learning for Graph Structured Data","created":"2020-02-03","cited_by_count":6},{"id":"1601.04692","title":"Spectral Theory of Unsigned and Signed Graphs. Applications to Graph Clustering: a Survey","created":"2016-01-18","cited_by_count":5},{"id":"1911.07494","title":"Change point localization in dependent dynamic nonparametric random dot product graphs","created":"2019-11-18","cited_by_count":5},{"id":"2101.05477","title":"Optimal network online change point localisation","created":"2021-01-14","cited_by_count":5},{"id":"1810.05973","title":"Sequential Change-point Detection for High-dimensional and non-Euclidean Data","created":"2018-10-14","cited_by_count":4},{"id":"1908.01823","title":"Change-point detection in dynamic networks via graphon estimation","created":"2019-08-05","cited_by_count":4},{"id":"1910.01722","title":"Constant State of Change: Engagement Inequality in Temporal Dynamic Networks","created":"2019-10-03","cited_by_count":3},{"id":"2110.06450","title":"Online network change point detection with missing values and temporal dependence","created":"2021-10-13","cited_by_count":3},{"id":"1910.02301","title":"Change Detection in Noisy Dynamic Networks: A Spectral Embedding Approach","created":"2019-10-05","cited_by_count":2},{"id":"1602.00661","title":"Detection and localization of change points in temporal networks with the aid of stochastic block models","created":"2016-02-01","cited_by_count":1},{"id":"1810.02906","title":"Network Distance Based on Laplacian Flows on Graphs","created":"2018-10-05","cited_by_count":1},{"id":"2007.10495","title":"Sorted Pooling in Convolutional Networks for One-shot Learning","created":"2020-07-20","cited_by_count":1},{"id":"2103.02680","title":"Weighted-Graph-Based Change Point Detection","created":"2021-03-03","cited_by_count":1},{"id":"2103.06347","title":"Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series","created":"2021-03-10","cited_by_count":1}],"next_cursor":null}