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Inference for multiple heterogeneous networks with a common invariant subspace., , , , , and . CoRR, (2019)Clustered Graph Matching for Label Recovery and Graph Classification., , , and . CoRR, (2022)Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks., , , , , , , , , and . SIAM J. Math. Data Sci., 5 (1): 77-96 (March 2023)Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question., , and . CoRR, (2020)Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace., , , , , and . J. Mach. Learn. Res., (2021)The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks., , , , , and . J. Mach. Learn. Res., (2022)Clustered Graph Matching for Label Recovery and Graph Classification., , , and . IEEE Trans. Netw. Sci. Eng., 10 (6): 3384-3395 (November 2023)Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks., , , and . J. Comput. Graph. Stat., 30 (4): 1111-1123 (2021)Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks., , , and . CoRR, (2018)Graph Matching Between Bipartite and Unipartite Networks: To Collapse, or Not to Collapse, That Is the Question., , and . IEEE Trans. Netw. Sci. Eng., 8 (4): 3019-3033 (2021)