Boolformer
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The first Transformer trained to perform end-to-end symbolic regression of Boolean functions.
End-to-end symbolic regression: Directly predicts compact Boolean formulas from input-output examples, skipping the typical search-over-programs loop of symbolic regression.
Handles complex functions: Produces compact formulas for complex Boolean functions that traditional symbolic-regression methods struggle to compress.
Gene regulatory networks: Applied to modeling the dynamics of gene regulatory networks, providing a concrete real-world application beyond synthetic benchmarks.
Transformer-as-symbolic-learner: Extends the "Transformer as symbolic regression engine" line started by earlier work on equation discovery, covering the discrete-logic case.
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