five

Hierarchical and partition datasets

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NIAID Data Ecosystem2026-03-12 收录
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https://zenodo.org/record/4898344
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The datasets used throughout the paper "Learning Dynamics of Hierarchical Category Structure in Deep Non-Linear Networks", submitted to NeurIPS 2021. These are synthetic datasets with hierarchical covariance structure (six hierarchies), P=936 features and C=64 categories (leaf node category). The hierarchical dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0001610_sigma_5.0000_norm_kemp_1_compressed.mat", while the partition dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0923671_sigma_5.0000_norm_kemp_1_compressed.mat". The data were generated in a manner similar to Kemp & Tenenbaum, 2008 and Saxe et al., 2019.
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2021-06-04
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