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Research questionHow can symbolic regression recover compact compositional formulas from noisy observations?Symbolic regression must search a large space of possible expressions while distinguishing structure from noise. Nested compositions make it difficult to recover formulas that are both accurate and simple.
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Latest papersRecent research connected to this question, newest first.SMILE: Bridging Continuous Optimization and Discrete Symbolic RecoveryThe paper presents a hybrid continuous-optimization and discrete-recovery procedure that analyzes compositional structure and distills learned representations into symbolic expressions. Evidence comes from ground-truth and black-box symbolic-regression datasets with component ablations; generalization beyond those settings is not established.research paper · Sep 4, 2026
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