Shoutout to @milescranmer.bsky.social's PySR, which made the task smoother! Open-source making the community stronger!

3/n: 🤖 SR combines analytic simplicity with the predictive capabilities of ML, providing a valuable tool for simplifying pheno analyses in colliders!

2/n: 🔬 QED provides a solid benchmark for validating SR against first principles. After this validation, we apply SR to Drell-Yan structure functions, deriving simple formulas as an alternative to methods like NNs (with many trainable parameters) or fixed functional forms

1/n: 🎯 How can machine learning simplify phenomenological analyses at the LHC? We explore symbolic regression (SR) as a tool to derive compact, precise analytic expressions. First stop: testing SR on quantum electrodynamics (QED).

Hi Ben, could I be added please?