Add ParentIndependentBinarySelectionModel #146
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This model learns position-specific log selection factors that are parent-independent, serving as a neural network analog to phylogenetic methods like Bloom & Neher (2023). Fixes #145 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]>
jgallowa07
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Jul 14, 2025
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The model has been tested, and the implementation looks good to me.
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Summary
ParentIndependentBinarySelectionModelclass that learns position-specific log selection factorsDetails
The model stores a learnable parameter tensor with shape
(max_seq_length, output_dim)or(max_seq_length,)depending on output dimension. During forward pass, it returns the appropriate slice expanded to match batch size, completely ignoring the parent sequence content.This provides a meaningful baseline between
SingleValueBinarySelectionModel(uniform selection) and transformer-based models (context-dependent selection).Fixes #145
🤖 Generated with Claude Code