{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/community-detection/papers/2","list_of":"/task/community-detection","task":"Community Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":10,"rows_per_page":100,"rows":[101,200],"of":919,"counts":{"archive_papers_tagged":919,"with_a_code_link":263,"where_syntology_ran_a_sample":16,"not_listed_spam_title":0,"listed":919,"listed_where_code_ran":16,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":14,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":14,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/community-detection","prev":"/task/community-detection","next":"/task/community-detection/papers/3","papers":[{"url":"/paper/hippocluster-an-efficient-hippocampus","slug":"hippocluster-an-efficient-hippocampus","title":"Hippocluster: an efficient, hippocampus-inspired algorithm for graph clustering","date":"2022-05-19","arxiv_id":"2205.12338","repositories_listed":1,"syntology":null},{"url":"/paper/perfect-spectral-clustering-with-discrete","slug":"perfect-spectral-clustering-with-discrete","title":"Perfect Spectral Clustering with Discrete Covariates","date":"2022-05-17","arxiv_id":"2205.08047","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-learning-unveils","slug":"self-supervised-learning-unveils","title":"Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slides","date":"2022-05-04","arxiv_id":"2205.01931","repositories_listed":1,"syntology":null},{"url":"/paper/enhance-ambiguous-community-structure-via","slug":"enhance-ambiguous-community-structure-via","title":"Enhance Ambiguous Community Structure via Multi-strategy Community Related Link Prediction Method with Evolutionary Process","date":"2022-04-28","arxiv_id":"2204.13301","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-learning-of-object-parts-for","slug":"self-supervised-learning-of-object-parts-for","title":"Self-Supervised Learning of Object Parts for Semantic Segmentation","date":"2022-04-27","arxiv_id":"2204.13101","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/self-supervised-learning-of-object-parts-for#ran","syntology_url":"https://syntology.ai/paper/2204.13101","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.13101"}},"official":{"repos":["mkuuwaujinga/leopart"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/a-hierarchical-block-distance-model-for-ultra","slug":"a-hierarchical-block-distance-model-for-ultra","title":"A Hierarchical Block Distance Model for Ultra Low-Dimensional Graph Representations","date":"2022-04-12","arxiv_id":"2204.05885","repositories_listed":1,"syntology":null},{"url":"/paper/correlation-based-feature-selection-to","slug":"correlation-based-feature-selection-to","title":"Correlation-based feature selection to identify functional dynamics in proteins","date":"2022-04-06","arxiv_id":"2204.02770","repositories_listed":1,"syntology":null},{"url":"/paper/cgc-contrastive-graph-clustering-for","slug":"cgc-contrastive-graph-clustering-for","title":"CGC: Contrastive Graph Clustering for Community Detection and Tracking","date":"2022-04-05","arxiv_id":"2204.08504","repositories_listed":1,"syntology":null},{"url":"/paper/learning-based-approaches-for-graph-problems","slug":"learning-based-approaches-for-graph-problems","title":"A Survey on Machine Learning Solutions for Graph Pattern Extraction","date":"2022-04-03","arxiv_id":"2204.01057","repositories_listed":1,"syntology":null},{"url":"/paper/properties-and-performance-of-the-abcde","slug":"properties-and-performance-of-the-abcde","title":"Properties and Performance of the ABCDe Random Graph Model with Community Structure","date":"2022-03-28","arxiv_id":"2203.14899","repositories_listed":1,"syntology":null},{"url":"/paper/machine-learning-based-objective-function","slug":"machine-learning-based-objective-function","title":"Machine-Learning Based Objective Function Selection for Community Detection","date":"2022-03-25","arxiv_id":"2203.13495","repositories_listed":1,"syntology":null},{"url":"/paper/facemap-towards-unsupervised-face-clustering","slug":"facemap-towards-unsupervised-face-clustering","title":"FaceMap: Towards Unsupervised Face Clustering via Map Equation","date":"2022-03-21","arxiv_id":"2203.10090","repositories_listed":1,"syntology":null},{"url":"/paper/sparse-random-hypergraphs-non-backtracking","slug":"sparse-random-hypergraphs-non-backtracking","title":"Sparse random hypergraphs: Non-backtracking spectra and community detection","date":"2022-03-14","arxiv_id":"2203.07346","repositories_listed":1,"syntology":null},{"url":"/paper/bayesian-community-detection-for-networks","slug":"bayesian-community-detection-for-networks","title":"Bayesian community detection for networks with covariates","date":"2022-03-04","arxiv_id":"2203.02090","repositories_listed":1,"syntology":null},{"url":"/paper/listing-maximal-k-plexes-in-large-real-world","slug":"listing-maximal-k-plexes-in-large-real-world","title":"Listing Maximal k-Plexes in Large Real-World Graphs","date":"2022-02-17","arxiv_id":"2202.08737","repositories_listed":1,"syntology":null},{"url":"/paper/graph-coloring-with-physics-inspired-graph","slug":"graph-coloring-with-physics-inspired-graph","title":"Graph Coloring with Physics-Inspired Graph Neural Networks","date":"2022-02-03","arxiv_id":"2202.01606","repositories_listed":1,"syntology":null},{"url":"/paper/modularity-aware-graph-autoencoders-for-joint","slug":"modularity-aware-graph-autoencoders-for-joint","title":"Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction","date":"2022-02-02","arxiv_id":"2202.00961","repositories_listed":1,"syntology":null},{"url":"/paper/classic-graph-structural-features-outperform","slug":"classic-graph-structural-features-outperform","title":"Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling","date":"2022-01-20","arxiv_id":"2201.08481","repositories_listed":1,"syntology":null},{"url":"/paper/vgaer-graph-neural-network-reconstruction","slug":"vgaer-graph-neural-network-reconstruction","title":"VGAER: Graph Neural Network Reconstruction based Community Detection","date":"2022-01-08","arxiv_id":"2201.04066","repositories_listed":1,"syntology":null},{"url":"/paper/what-knowledge-can-be-transferred-between","slug":"what-knowledge-can-be-transferred-between","title":"Network Collaborator: Knowledge Transfer Between Network Reconstruction and Community Detection","date":"2022-01-04","arxiv_id":"2201.01134","repositories_listed":1,"syntology":null},{"url":"/paper/a-spectral-method-for-joint-community","slug":"a-spectral-method-for-joint-community","title":"A Spectral Method for Joint Community Detection and Orthogonal Group Synchronization","date":"2021-12-25","arxiv_id":"2112.13199","repositories_listed":1,"syntology":null},{"url":"/paper/the-interplay-between-ranking-and-communities","slug":"the-interplay-between-ranking-and-communities","title":"The interplay between ranking and communities in networks","date":"2021-12-23","arxiv_id":"2112.12670","repositories_listed":1,"syntology":null},{"url":"/paper/descriptive-vs-inferential-community","slug":"descriptive-vs-inferential-community","title":"Descriptive vs. inferential community detection in networks: pitfalls, myths, and half-truths","date":"2021-11-30","arxiv_id":"2112.00183","repositories_listed":1,"syntology":null},{"url":"/paper/graph-communal-contrastive-learning","slug":"graph-communal-contrastive-learning","title":"Graph Communal Contrastive Learning","date":"2021-10-28","arxiv_id":"2110.14863","repositories_listed":1,"syntology":null},{"url":"/paper/vaccine-skepticism-detection-by-network","slug":"vaccine-skepticism-detection-by-network","title":"Vaccine skepticism detection by network embedding","date":"2021-10-20","arxiv_id":"2110.13619","repositories_listed":1,"syntology":null},{"url":"/paper/robustness-modularity-in-complex-networks","slug":"robustness-modularity-in-complex-networks","title":"Robustness modularity in complex networks","date":"2021-10-05","arxiv_id":"2110.02297","repositories_listed":1,"syntology":null},{"url":"/paper/clique-percolation-method-memory-efficient","slug":"clique-percolation-method-memory-efficient","title":"Clique percolation method: memory efficient almost exact communities","date":"2021-10-04","arxiv_id":"2110.01213","repositories_listed":1,"syntology":null},{"url":"/paper/transfer-learning-based-multi-objective","slug":"transfer-learning-based-multi-objective","title":"Transfer Learning Based Multi-Objective Genetic Algorithm for Dynamic Community Detection","date":"2021-09-30","arxiv_id":"2109.15136","repositories_listed":1,"syntology":null},{"url":"/paper/memory-efficient-convex-optimization-for-self","slug":"memory-efficient-convex-optimization-for-self","title":"Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach","date":"2021-09-23","arxiv_id":"2109.11135","repositories_listed":1,"syntology":null},{"url":"/paper/popularity-adjusted-block-models-are","slug":"popularity-adjusted-block-models-are","title":"Popularity Adjusted Block Models are Generalized Random Dot Product Graphs","date":"2021-09-09","arxiv_id":"2109.04010","repositories_listed":1,"syntology":null},{"url":"/paper/abcde-approximating-betweenness-centrality","slug":"abcde-approximating-betweenness-centrality","title":"ABCDE: Approximating Betweenness-Centrality ranking with progressive-DropEdge","date":"2021-09-06","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/detecting-communities-from-heterogeneous","slug":"detecting-communities-from-heterogeneous","title":"Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model","date":"2021-09-05","arxiv_id":"2109.02058","repositories_listed":1,"syntology":null},{"url":"/paper/scalable-community-detection-via-parallel","slug":"scalable-community-detection-via-parallel","title":"Scalable Community Detection via Parallel Correlation Clustering","date":"2021-07-27","arxiv_id":"2108.01731","repositories_listed":1,"syntology":null},{"url":"/paper/the-hyperspherical-geometry-of-community","slug":"the-hyperspherical-geometry-of-community","title":"The Hyperspherical Geometry of Community Detection: Modularity as a Distance","date":"2021-07-06","arxiv_id":"2107.02645","repositories_listed":1,"syntology":null},{"url":"/paper/subspace-clustering-based-analysis-of-neural","slug":"subspace-clustering-based-analysis-of-neural","title":"Subspace Clustering Based Analysis of Neural Networks","date":"2021-07-02","arxiv_id":"2107.01296","repositories_listed":1,"syntology":null},{"url":"/paper/a-deep-latent-space-model-for-graph","slug":"a-deep-latent-space-model-for-graph","title":"A Deep Latent Space Model for Graph Representation Learning","date":"2021-06-22","arxiv_id":"2106.11721","repositories_listed":1,"syntology":null},{"url":"/paper/rank-one-matrix-estimation-with-groupwise","slug":"rank-one-matrix-estimation-with-groupwise","title":"Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticity","date":"2021-06-22","arxiv_id":"2106.11950","repositories_listed":1,"syntology":null},{"url":"/paper/spectral-goodness-of-fit-tests-for-complete","slug":"spectral-goodness-of-fit-tests-for-complete","title":"Spectral goodness-of-fit tests for complete and partial network data","date":"2021-06-17","arxiv_id":"2106.09702","repositories_listed":1,"syntology":null},{"url":"/paper/joint-community-detection-and-rotational","slug":"joint-community-detection-and-rotational","title":"Joint Community Detection and Rotational Synchronization via Semidefinite Programming","date":"2021-05-13","arxiv_id":"2105.06031","repositories_listed":1,"syntology":null},{"url":"/paper/semidefinite-programming-for-community","slug":"semidefinite-programming-for-community","title":"Semidefinite Programming for Community Detection with Side Information","date":"2021-05-06","arxiv_id":"2105.02816","repositories_listed":1,"syntology":null},{"url":"/paper/recurrent-graph-neural-network-algorithm-for","slug":"recurrent-graph-neural-network-algorithm-for","title":"Recurrent Graph Neural Network Algorithm for Unsupervised Network Community Detection","date":"2021-03-03","arxiv_id":"2103.02520","repositories_listed":1,"syntology":null},{"url":"/paper/graph-community-detection-from-coarse","slug":"graph-community-detection-from-coarse","title":"Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model","date":"2021-02-25","arxiv_id":"2102.13135","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-in-weighted-multilayer","slug":"community-detection-in-weighted-multilayer","title":"Community Detection in Weighted Multilayer Networks with Ambient Noise","date":"2021-02-24","arxiv_id":"2103.00486","repositories_listed":1,"syntology":null},{"url":"/paper/hide-and-seek-outwitting-community-detection","slug":"hide-and-seek-outwitting-community-detection","title":"Hide and Seek: Outwitting Community Detection Algorithms","date":"2021-02-22","arxiv_id":"2102.10759","repositories_listed":1,"syntology":null},{"url":"/paper/local-hyper-flow-diffusion","slug":"local-hyper-flow-diffusion","title":"Local Hyper-Flow Diffusion","date":"2021-02-16","arxiv_id":"2102.07945","repositories_listed":1,"syntology":null},{"url":"/paper/characterizing-and-comparing-external","slug":"characterizing-and-comparing-external","title":"Characterizing and comparing external measures for the assessment of cluster analysis and community detection","date":"2021-02-01","arxiv_id":"2102.00708","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-in-the-stochastic-block","slug":"community-detection-in-the-stochastic-block","title":"Community Detection in the Stochastic Block Model by Mixed Integer Programming","date":"2021-01-26","arxiv_id":"2101.12336","repositories_listed":1,"syntology":null},{"url":"/paper/informative-core-identification-in-complex","slug":"informative-core-identification-in-complex","title":"Informative core identification in complex networks","date":"2021-01-16","arxiv_id":"2101.06388","repositories_listed":1,"syntology":null},{"url":"/paper/variational-embeddings-for-community","slug":"variational-embeddings-for-community","title":"Variational Embeddings for Community Detection and Node Representation","date":"2021-01-11","arxiv_id":"2101.03885","repositories_listed":1,"syntology":null},{"url":"/paper/disentangling-homophily-community-structure","slug":"disentangling-homophily-community-structure","title":"Disentangling homophily, community structure and triadic closure in networks","date":"2021-01-07","arxiv_id":"2101.02510","repositories_listed":1,"syntology":null},{"url":"/paper/modularity-maximisation-for-graphons","slug":"modularity-maximisation-for-graphons","title":"Modularity maximisation for graphons","date":"2021-01-02","arxiv_id":"2101.00503","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-using-fast-low-1","slug":"community-detection-using-fast-low-1","title":"Community detection using fast low-cardinality semidefinite programming","date":"2020-12-04","arxiv_id":"2012.02676","repositories_listed":1,"syntology":null},{"url":"/paper/self-expressive-graph-neural-network-for","slug":"self-expressive-graph-neural-network-for","title":"Unsupervised Constrained Community Detection via Self-Expressive Graph Neural Network","date":"2020-11-28","arxiv_id":"2011.14078","repositories_listed":1,"syntology":null},{"url":"/paper/mixed-membership-graph-clustering-via","slug":"mixed-membership-graph-clustering-via","title":"Mixed Membership Graph Clustering via Systematic Edge Query","date":"2020-11-25","arxiv_id":"2011.12988","repositories_listed":1,"syntology":null},{"url":"/paper/sparsity-aware-robust-community-detection","slug":"sparsity-aware-robust-community-detection","title":"Sparsity-aware Robust Community Detection(SPARCODE)","date":"2020-11-18","arxiv_id":"2011.09196","repositories_listed":1,"syntology":null},{"url":"/paper/spectral-clustering-on-spherical-coordinates","slug":"spectral-clustering-on-spherical-coordinates","title":"Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel","date":"2020-11-09","arxiv_id":"2011.04558","repositories_listed":1,"syntology":null},{"url":"/paper/phylogenetic-reconstruction-of-the-cultural","slug":"phylogenetic-reconstruction-of-the-cultural","title":"Phylogenetic reconstruction of the cultural evolution of electronic music via dynamic community detection (1975-1999)","date":"2020-11-04","arxiv_id":"2011.02460","repositories_listed":1,"syntology":null},{"url":"/paper/fast-network-community-detection-with-profile","slug":"fast-network-community-detection-with-profile","title":"Fast Network Community Detection with Profile-Pseudo Likelihood Methods","date":"2020-11-01","arxiv_id":"2011.00647","repositories_listed":1,"syntology":null},{"url":"/paper/investigating-annotator-bias-with-a-graph","slug":"investigating-annotator-bias-with-a-graph","title":"Investigating Annotator Bias with a Graph-Based Approach","date":"2020-11-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/on-graph-neural-networks-versus-graph-1","slug":"on-graph-neural-networks-versus-graph-1","title":"On Graph Neural Networks versus Graph-Augmented MLPs","date":"2020-10-28","arxiv_id":"2010.15116","repositories_listed":1,"syntology":null},{"url":"/paper/joint-inference-of-structure-and-diffusion-in","slug":"joint-inference-of-structure-and-diffusion-in","title":"Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization","date":"2020-10-03","arxiv_id":"2010.01400","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-pattern-recognition-and","slug":"community-detection-pattern-recognition-and","title":"Community detection, pattern recognition, and hypergraph-based learning: approaches using metric geometry and persistent homology","date":"2020-09-29","arxiv_id":"2010.00435","repositories_listed":1,"syntology":null},{"url":"/paper/overlapping-community-detection-in-networks-1","slug":"overlapping-community-detection-in-networks-1","title":"Overlapping community detection in networks via sparse spectral decomposition","date":"2020-09-20","arxiv_id":"2009.10641","repositories_listed":1,"syntology":null},{"url":"/paper/hierarchical-community-structure-in-networks","slug":"hierarchical-community-structure-in-networks","title":"Hierarchical community structure in networks","date":"2020-09-15","arxiv_id":"2009.07196","repositories_listed":1,"syntology":null},{"url":"/paper/hierarchical-message-passing-graph-neural","slug":"hierarchical-message-passing-graph-neural","title":"Hierarchical Message-Passing Graph Neural Networks","date":"2020-09-08","arxiv_id":"2009.03717","repositories_listed":1,"syntology":null},{"url":"/paper/online-community-detection-for-event-streams","slug":"online-community-detection-for-event-streams","title":"Online Estimation and Community Detection of Network Point Processes for Event Streams","date":"2020-09-03","arxiv_id":"2009.01742","repositories_listed":1,"syntology":null},{"url":"/paper/multiverse-a-multiplex-and-multiplex","slug":"multiverse-a-multiplex-and-multiplex","title":"MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach","date":"2020-08-23","arxiv_id":"2008.10085","repositories_listed":1,"syntology":null},{"url":"/paper/almost-exact-recovery-in-noisy-semi","slug":"almost-exact-recovery-in-noisy-semi","title":"Almost exact recovery in noisy semi-supervised learning","date":"2020-07-29","arxiv_id":"2007.14717","repositories_listed":1,"syntology":null},{"url":"/paper/integrating-network-embedding-and-community","slug":"integrating-network-embedding-and-community","title":"Integrating Network Embedding and Community Outlier Detection via Multiclass Graph Description","date":"2020-07-20","arxiv_id":"2007.10231","repositories_listed":1,"syntology":null},{"url":"/paper/extended-stochastic-block-models","slug":"extended-stochastic-block-models","title":"Extended Stochastic Block Models with Application to Criminal Networks","date":"2020-07-16","arxiv_id":"2007.08569","repositories_listed":1,"syntology":null},{"url":"/paper/incnsa-detecting-communities-incrementally","slug":"incnsa-detecting-communities-incrementally","title":"IncNSA: Detecting communities incrementally from time-evolving networks based on node similarity","date":"2020-07-16","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/on-identifying-unobserved-heterogeneity-in","slug":"on-identifying-unobserved-heterogeneity-in","title":"On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariates","date":"2020-07-04","arxiv_id":"2007.02156","repositories_listed":1,"syntology":null},{"url":"/paper/non-convex-exact-community-recovery-in","slug":"non-convex-exact-community-recovery-in","title":"Non-Convex Exact Community Recovery in Stochastic Block Model","date":"2020-06-29","arxiv_id":"2006.15843","repositories_listed":1,"syntology":null},{"url":"/paper/statistical-inference-of-assortative","slug":"statistical-inference-of-assortative","title":"Statistical inference of assortative community structures","date":"2020-06-25","arxiv_id":"2006.14493","repositories_listed":1,"syntology":null},{"url":"/paper/tangles-from-weak-to-strong-clustering","slug":"tangles-from-weak-to-strong-clustering","title":"Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees","date":"2020-06-25","arxiv_id":"2006.14444","repositories_listed":1,"syntology":null},{"url":"/paper/strongly-local-p-norm-cut-algorithms-for-semi","slug":"strongly-local-p-norm-cut-algorithms-for-semi","title":"Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering","date":"2020-06-15","arxiv_id":"2006.08569","repositories_listed":1,"syntology":null},{"url":"/paper/interferometric-graph-transform-a-deep","slug":"interferometric-graph-transform-a-deep","title":"Interferometric Graph Transform: a Deep Unsupervised Graph Representation","date":"2020-06-10","arxiv_id":"2006.05722","repositories_listed":1,"syntology":null},{"url":"/paper/graph-neural-network-encoding-for-community","slug":"graph-neural-network-encoding-for-community","title":"Graph Neural Network Encoding for Community Detection in Attribute Networks","date":"2020-06-06","arxiv_id":"2006.03996","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-in-sparse-time-evolving","slug":"community-detection-in-sparse-time-evolving","title":"Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian","date":"2020-06-03","arxiv_id":"2006.04510","repositories_listed":1,"syntology":null},{"url":"/paper/revealing-consensus-and-dissensus-between","slug":"revealing-consensus-and-dissensus-between","title":"Revealing consensus and dissensus between network partitions","date":"2020-05-28","arxiv_id":"2005.13977","repositories_listed":1,"syntology":null},{"url":"/paper/deep-learning-for-community-detection","slug":"deep-learning-for-community-detection","title":"Deep Learning for Community Detection: Progress, Challenges and Opportunities","date":"2020-05-17","arxiv_id":"2005.08225","repositories_listed":1,"syntology":null},{"url":"/paper/assortative-constrained-stochastic-block","slug":"assortative-constrained-stochastic-block","title":"Assortative-Constrained Stochastic Block Models","date":"2020-04-21","arxiv_id":"2004.11890","repositories_listed":1,"syntology":null},{"url":"/paper/recommendation-system-using-a-deep-learning","slug":"recommendation-system-using-a-deep-learning","title":"Recommendation system using a deep learning and graph analysis approach","date":"2020-04-17","arxiv_id":"2004.08100","repositories_listed":1,"syntology":null},{"url":"/paper/inference-in-the-stochastic-block-model-with","slug":"inference-in-the-stochastic-block-model-with","title":"Reliable Time Prediction in the Markov Stochastic Block Model","date":"2020-04-09","arxiv_id":"2004.04402","repositories_listed":1,"syntology":null},{"url":"/paper/gossip-and-attend-context-sensitive-graph","slug":"gossip-and-attend-context-sensitive-graph","title":"Gossip and Attend: Context-Sensitive Graph Representation Learning","date":"2020-03-30","arxiv_id":"2004.00413","repositories_listed":1,"syntology":null},{"url":"/paper/a-unified-framework-for-spectral-clustering","slug":"a-unified-framework-for-spectral-clustering","title":"A unified framework for spectral clustering in sparse graphs","date":"2020-03-20","arxiv_id":"2003.09198","repositories_listed":1,"syntology":null},{"url":"/paper/merge-split-markov-chain-monte-carlo-for","slug":"merge-split-markov-chain-monte-carlo-for","title":"Merge-split Markov chain Monte Carlo for community detection","date":"2020-03-16","arxiv_id":"2003.07070","repositories_listed":1,"syntology":null},{"url":"/paper/analysis-of-researchgate-a-community","slug":"analysis-of-researchgate-a-community","title":"Analysis of ResearchGate, A Community Detection Approach","date":"2020-03-12","arxiv_id":"2003.05591","repositories_listed":1,"syntology":null},{"url":"/paper/parameterized-objectives-and-algorithms-for","slug":"parameterized-objectives-and-algorithms-for","title":"Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs","date":"2020-02-21","arxiv_id":"2002.09460","repositories_listed":1,"syntology":null},{"url":"/paper/simultaneous-prediction-and-community","slug":"simultaneous-prediction-and-community","title":"Simultaneous prediction and community detection for networks with application to neuroimaging","date":"2020-02-05","arxiv_id":"2002.01645","repositories_listed":1,"syntology":null},{"url":"/paper/louvainne-hierarchical-louvain-method-for-1","slug":"louvainne-hierarchical-louvain-method-for-1","title":"LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding","date":"2020-02-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/graph-neighborhood-attentive-pooling-1","slug":"graph-neighborhood-attentive-pooling-1","title":"Graph Neighborhood Attentive Pooling","date":"2020-01-28","arxiv_id":"2001.10394","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-attack-on-community-detection-by","slug":"adversarial-attack-on-community-detection-by","title":"Adversarial Attack on Community Detection by Hiding Individuals","date":"2020-01-22","arxiv_id":"2001.07933","repositories_listed":1,"syntology":null},{"url":"/paper/community-detection-in-bipartite-networks","slug":"community-detection-in-bipartite-networks","title":"Community Detection in Bipartite Networks with Stochastic Blockmodels","date":"2020-01-22","arxiv_id":"2001.11818","repositories_listed":1,"syntology":null},{"url":"/paper/louvainne-hierarchical-louvain-method-for","slug":"louvainne-hierarchical-louvain-method-for","title":"LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding.","date":"2020-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/p-norm-flow-diffusion-for-local-graph-1","slug":"p-norm-flow-diffusion-for-local-graph-1","title":"p-Norm Flow Diffusion for Local Graph Clustering","date":"2020-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/a-non-negative-symmetric-encoder-decoder","slug":"a-non-negative-symmetric-encoder-decoder","title":"A Non-negative Symmetric Encoder-Decoder Approach for Community Detection","date":"2019-12-24","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/bridging-the-gap-between-community-and-node","slug":"bridging-the-gap-between-community-and-node","title":"Bridging the Gap between Community and Node Representations: Graph Embedding via Community Detection","date":"2019-12-17","arxiv_id":"1912.08808","repositories_listed":1,"syntology":null},{"url":"/paper/rem-from-structural-entropy-to-community","slug":"rem-from-structural-entropy-to-community","title":"REM: From Structural Entropy to Community Structure Deception","date":"2019-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-co-learning-on-g-manifolds","slug":"unsupervised-co-learning-on-g-manifolds","title":"Unsupervised Co-Learning on G-Manifolds Across Irreducible Representations","date":"2019-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null}],"record_sha256":"e72478caa5c951a141878d4c605ec58ea540ad20fa9766fe47c1c362fb65fa65","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}