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Two pooling baselines over sequence_v2 fields and static tensors, built on SequenceEmbeddingModel. - Unified_LogisticRegression embeds each level, mean-pools the records of every group bottom-up (an empty group gives zeros), concatenates the field summaries with the raw static vectors, and applies one linear layer. - Unified_MLP adds an MLP at every level and on each static field before pooling; hidden_dim, num_layers and dropout are set per field. - Per-step labels: each label record uses the mean of the top-level records at or before its time (a prefix mean), so it never sees later records. Fields need a series top level.
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Sixth PR in the stack toward a unified sequence representation, on top of #1354. It adds two pooling baselines over
sequence_v2fields and static tensors, built onSequenceEmbeddingModel.Changes
Unified_LogisticRegressionembeds each level and mean-pools the records of every group bottom-up (an empty group gives zeros). It concatenates the field summaries with the raw static vectors and applies one linear layer.Unified_MLPadds an MLP at every level and on each static field before pooling.hidden_dim,num_layersanddropoutare set per field.seriestop level.pyhealth.modelsand listed in the model guide, with API pages.