{"total":17,"rows":[{"id":"2105.00987","title":"Spectral clustering under degree heterogeneity: a case for the random walk Laplacian","created":"2021-05-03","cited_by_count":7,"area":null},{"id":"2106.01260","title":"Matrix factorisation and the interpretation of geodesic distance","created":"2021-06-02","cited_by_count":6,"area":null},{"id":"2105.10838","title":"Hypothesis Testing for Equality of Latent Positions in Random Graphs","created":"2021-05-23","cited_by_count":5,"area":null},{"id":"2306.06155","title":"Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks","created":"2023-06-09","cited_by_count":5,"area":null},{"id":"2101.07354","title":"Exact Recovery of Community Structures Using DeepWalk and Node2vec","created":"2021-01-18","cited_by_count":2,"area":null},{"id":"2205.03486","title":"Clustered Graph Matching for Label Recovery and Graph Classification","created":"2022-05-06","cited_by_count":2,"area":null},{"id":"2203.14223","title":"Identifying Peer Influence in Therapeutic Communities Adjusting for Latent Homophily","created":"2022-03-27","cited_by_count":1,"area":null},{"id":"2210.15277","title":"Implications of sparsity and high triangle density for graph representation learning","created":"2022-10-27","cited_by_count":1,"area":null},{"id":"2211.00128","title":"SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals","created":"2022-10-31","cited_by_count":1,"area":null},{"id":"2312.11054","title":"Detection of Model-based Planted Pseudo-cliques in Random Dot Product Graphs by the Adjacency Spectral Embedding and the Graph Encoder Embedding","created":"2023-12-18","cited_by_count":1,"area":null},{"id":"2101.02180","title":"Maximum a Posteriori Inference of Random Dot Product Graphs via Conic Programming","created":"2021-01-06","cited_by_count":0,"area":null},{"id":"2201.01689","title":"Asymptotics of $\\ell_2$ Regularized Network Embeddings","created":"2022-01-05","cited_by_count":0,"area":null},{"id":"2202.03945","title":"Spectral embedding and the latent geometry of multipartite networks","created":"2022-02-08","cited_by_count":0,"area":null},{"id":"2208.09710","title":"Adversarial contamination of networks in the setting of vertex nomination: a new trimming method","created":"2022-08-20","cited_by_count":0,"area":null},{"id":"2208.13921","title":"Dynamic Network Sampling for Community Detection","created":"2022-08-29","cited_by_count":0,"area":null},{"id":"2602.21055","title":"Adjacency Spectral Embeddings of Correlation Networks","created":"2026-02-24","cited_by_count":0,"area":null},{"id":"2605.22346","title":"The ASE-LSE Disagreement Landscape: An End-to-End Characterisation of Extremes and Structural Drivers","created":"2026-05-21","cited_by_count":0,"area":null}],"next_cursor":null}